Crack detection is an important application for Ground penetrating radar (GPR) to examine the concrete road or building structure conditions. The layer of rebars or utility pipes that typically exist inside the concrete structure can generate stronger scattering than small concrete cracks to affect detection effectiveness. In GPR image, the signature patterns of regularly distributed rebars or pipes can be deemed as correlated background signals, while for the small size cracks, their image features are typically irregularly and sparsely distributed. To effectively detect the cracks in concrete structure, the robust principal component analysis algorithm is developed to characterize the rank and sparsity of GPR image. For performance evaluations, simulations are conducted with various configurations.

In this paper, an object characterization method based on neural networks is developed for GPR subsurface imaging. Currently, most existing studies demonstrate detecting and imaging objects of cylindrical shapes. While in this paper, no restriction is imposed on the object shape. Three neural network algorithms are exploited to characterize different types of object signatures, including object shape, object material, object size, object depth and subsurface medium’s dielectric constant. Feature extraction is performed to characterize the instantaneous amplitude and time delay of the reflection signal from the object. The characterization method is evaluated utilizing the data synthesized with the finite-difference timedomain (FDTD) simulator.

The use of microwave and radar sensors in the nondestructive evaluation (NDE) of damaged materials and structures has been proven to be a promising approach. In this paper, a portable imaging radar sensor utilizing 10 GHz central frequency and stripmap synthetic aperture radar (SAR) imaging was applied to steel and wood specimens for size and range determination. Relationships between range and properties of SAR images (e.g. maximum amplitude and total SAR amplitude) were developed and reported for various specimens including a steel bar (2.5 cm by 2.5 cm by 28.5 cm), a wood bar (2.5 cm by 2.5 cm by 28.5 cm), a steel plate (39.7 cm by 57.9 cm by 1.75 cm), and a wood board (30.5 cm by 30.5 cm by 1.8 cm). Various ranges from 30 cm to 100 cm were used on these specimens. In our experiment, attenuation of radar signals collected by the imaging radar system on different material specimens was measured and modeled. Change in the attenuation of maximum SAR amplitude was observed in different materials. It is found that SAR images can be used to distinguish materials of different compositions and sizes.

The aerospace industry has been investigating the use of brazing for structural joints, as a mean of reducing cost and weight. There therefore is a need for a rapid, robust, and cost-effective non-destructive testing method for evaluating the structural integrity of the joints. The mechanical strength of brazed joints depends mainly on the amount of brittle phases in their microstructure. Ultrasonic guided waves offer the possibility of detecting brittle phases in joints using spatio-temporal measurements. Moreover, they offer the opportunity to inspect complex shape joints. This study focused on the development of a technique based on ultrasonic guided waves for the inspection of Inconel 625 lap joints brazed with BNi-2 filler metal. A finite element model of a lap joint was used to optimize the inspection parameters and assess the feasibility of detecting the amount of brittle phases in the joint. A finite element parametric study simulating the input signal shape, the center frequency, and the excitation direction was performed. The simulations showed that the ultrasonic guided wave energy transmitted through, and reflected from, the joints was proportional to the amount of brittle phases in the joint.

The spline component of gearbox structure is a non-redundant element that requires early detection of flaws for preventing catastrophic failures. The acoustic emission (AE) method is a direct way of detecting active flaws; however, the method suffers from the influence of background noise and location/sensor based pattern recognition method. It is important to identify the source mechanism and adapt it to different test conditions and sensors. In this paper, the fatigue crack growth of a notched and flattened gearbox spline component is monitored using the AE method in a laboratory environment. The test sample has the major details of the spline component on a flattened geometry. The AE data is continuously collected together with strain gauges strategically positions on the structure. The fatigue test characteristics are 4 Hz frequency and 0.1 as the ratio of minimum to maximum loading in tensile regime. It is observed that there are significant amount of continuous emissions released from the notch tip due to the formation of plastic deformation and slow crack growth. The frequency spectra of continuous emissions and burst emissions are compared to understand the difference of sudden crack growth and gradual crack growth. The predicted crack growth rate is compared with the AE data using the cumulative AE events at the notch tip. The source mechanism of sudden crack growth is obtained solving the inverse mathematical problem from output signal to input signal. The spline component of gearbox structure is a non-redundant element that requires early detection of flaws for preventing catastrophic failures. In this paper, the fatigue crack growth of a notched and flattened gearbox spline component is monitored using the AE method The AE data is continuously collected together with strain gauges. There are significant amount of continuous emissions released from the notch tip due to the formation of plastic deformation and slow crack growth. The source mechanism of sudden crack growth is obtained solving the inverse mathematical problem from output signal to input signal.

A unified approach was formulated to predict guided-wave propagation in a material regardless its degree of anisotropy, thereby having one solution method for both isotropic and anisotropic material. The unified approach was based on the coupled eigenvalue problem derived from Chirstoffels equation for a lamina. The eigenvalue problem yielded a set of eigenvalues, and corresponding eigenvectors that were used to obtain the stress-displacement matrix. The dispersion curves were obtained by applying the traction free boundary conditions to the stress-displacement matrix, and searching for sign changes in the complex determinant of the matrix. To search for sign changes, hence the velocity-wavenumber pairs which yielded a solution to the problem, the real and imaginary part of the complex determinant had to change sign simultaneously. A phase angle approach was, therefore, developed and successfully applied. A refinement algorithm was applied to refine the accuracy of the solution without increasing the computational time significantly. A high accuracy was required to calculated the correct partial-wave participation factors. The obtained partial-wave participation factors were used to calculate the modeshape through the thickness for each velocity-wavenumber pair. To identify the different wave types, A0, S0, SHS0, SHA0, a modeshape identification was applied successfully. The unified approach was evaluated for hybrid aerospace composites. In addition, the two most common solution methods: (i) the global matrix method; and (ii) the transfer matrix method were applied, and a comparative study between the different methods was performed.

Pervasive smartphones have demonstrated great potential in structural health monitoring (SHM) of civil infrastructures. Their sensing, processing, and communication capabilities along with crowdsourcing facility ease technical difficulties and reduce financial burdens of instrumentation and monitoring for SHM in civil infrastructures. However, smartphones are vulnerable to unintentional misuses and malicious attacks. This paper analyzes the vulnerabilities of smartphones in performing SHM and reveals the exploitation of those vulnerabilities. The work probes the attack surface of both devices and data. Device attack scenarios include hacking individual smartphones to modify the data stored on them and orchestrating smartphones to launch a distributed denial-of-service attack. Specifically, experiments are conducted to remotely access an Android smartphone and modify the sensing data of structural health stored on it. The work also presents a case study that reveals the sensitivity of a popular perturbation analysis method to faulty data delivered by a smartphone. The paper provides the direction of meeting the security challenge to using smartphones for SHM. As the first line of defense, device authentication is implemented in the smartphone to stop spoofing. Subsequently, message authentication is devised to maintain data integrity. There is a need to apply data science for the SHM immunity system against the sensitivity to data inaccuracy. The work also evaluates the cost-effectiveness of the proposed security measures, recommending varying levels of security to mitigate the adversaries to smartphones used in SHM systems. It calls for security solutions at the design stage of SHM systems rather than patching up after their implementations.

A country’s economic development depends heavily on transportation networks and hence, as a vital aspect, bridge structures must function safely at all times. Structural Health Monitoring (SHM) and Damage Prognosis (DP) of bridges should be a priority in order to prevent deterioration, avoid collapse and ensure user’s safety. One objective of SHM for civil structures is the behavior assessment due to ambient, operational and seismic excitations, for which acceptable ranges are established for the variation of dynamic properties. Through Operational Modal Analysis (OMA) it is possible to estimate operational frequencies of a bridge and provide a measure of its current dynamic behavior. These frequencies can then be used for future comparisons to revise if the structure has been damaged or has experienced changes due to environmental conditions. In this paper, vertical and horizontal operational frequencies of more than 300 vehicular and pedestrian bridges of the transportation network of Santiago de Cali, Colombia, were estimated using ambient vibration tests. Data were obtained using smartphones and processed using frequency domain analyses. Correlations of these frequencies with the structural characteristics of the bridges are presented. The results of this study represent the current state of each bridge and provide a baseline for future evaluations of changes due to environmental conditions or damage.

This paper presents the implementation of an updating procedure for the finite element model (FEM) of a prestressed concrete continuous box-girder highway off-ramp bridge. Ambient vibration testing was conducted to excite the bridge, assisted by linear chirp sweepings induced by two small electrodynamic shakes deployed to enhance the excitation levels, since the bridge was closed to traffic. The data-driven stochastic subspace identification method was executed to recover the modal properties from measurement data. An initial FEM was developed and correlation between the experimental modal results and their analytical counterparts was studied. Modelling of the pier and abutment bearings was carefully adjusted to reflect the real operational conditions of the bridge. The subproblem approximation method was subsequently utilized to automatically update the FEM. For this purpose, the influences of bearing stiffness, and mass density and Young’s modulus of materials were examined as uncertain parameters using sensitivity analysis. The updating objective function was defined based on a summation of squared values of relative errors of natural frequencies between the FEM and experimentation. All the identified modes were used as the target responses with the purpose of putting more constrains for the optimization process and decreasing the number of potentially feasible combinations for parameter changes. The updated FEM of the bridge was able to produce sufficient improvements in natural frequencies in most modes of interest, and can serve for a more precise dynamic response prediction or future investigation of the bridge health.

A Particle Swarm Optimization (PSO) algorithm is used to improve sensors placement in an ultrasonic Structural Health Monitoring (SHM) system where the detection is performed through the beam-forming imaging algorithm. The imaging algorithm reconstructs the defect image and estimates its location based on analytically generated signals, considering circular through hole damage in an aluminum plate as the tested structure. Then, the PSO algorithm changes the position of sensors to improve the accuracy of the detection. Thus, the two algorithms are working together iteratively to optimize the system configuration, taking into account a complete modeling of the SHM system. It is shown that this approach can provide good sensors placements for detection of multiple defects in the target area, and for different numbers of sensors.

The U.S. transportation infrastructure has many wrought iron truss bridges that are more than a century old and still remain in use. Understanding the structural properties and identifying the health conditions of these historical bridges are essential to deciding the maintenance or rebuild plan of the bridges. This research involved an on-site full-scale system identification test case study on the historical Old Alton Bridge (a wrought iron truss bridge built in 1884 in Denton, Texas) using a wireless sensor network. The study results demonstrate a practical and convenient experimental system identification method for historical bridge structures. The method includes the basic steps of the in-situ experiment and in-house data analysis. Various excitation methods are studied for field testing, including ambient vibration by wind load, forced vibration by human jumping load, and forced vibration by human pulling load. Structural responses of the bridge under these different excitation approaches were analyzed and compared with numerical analysis results.

It has been shown that the variations of structural properties due to changing environmental conditions such as temperature can be as significant as those caused by structural damage and even liveload. Therefore, tracking changes that are correlated with environmental variations is a necessary step in order to detect and assess structural damage in addition to the normal structural response to traffic. In this paper, daily measurement data that is collected from the concrete towers of the Ironton-Russell Bridge will be presented and correlation of the collected measurement data and temperature will be overviewed. Variation of the daily thermal response of tower concrete walls will be compared with the daily thermal responses of the steel box within the tower and finally, thermal coefficient for compensating the thermal induced responses will be estimated.

The maintenance and repair of wind energy converters is a significant cost factor. Therefore it is mandatory to minimise the downtime caused by unnoticed faults. A key contributor to the load on the wind turbine installation and to material fatigue is the plant´s unavoidable vibration. We report about a development of a new 1.5 μm laser vibrometer system to measure vibrations of rotating blades of wind turbines up to a distance of several hundred meters - based on a very precise imaged tracking system.

In this paper, the integrity of a wind turbine tower (WTT) structure is nondestructively estimated using its vibration responses. Firstly, a damage detection algorithm using changes in modal characteristics to predict damage locations and severities in structures is outlined. Secondly, a finite element (FE) model based on a real WTT structure is established by using a commercial software, Midas FEA. Thirdly, forced vibration tests are performed on the FE model of the WTT structure under various damage scenarios. The changes in modal parameters such as natural frequencies and mode shapes are examined for damage monitoring in the structure. Finally, the feasibility of the vibration-based damage detection method is numerically verified by predicting locations and severities of the damage in the FE model of the WTT structure.

Six wind turbines were blown to the ground by the wind gust during the attack of Typhoon Soudelor in August 2015. Survey using unmanned aerial vehicle, UAV, found the collapsed wind turbines had been broken at the lower section of the supporting towers. The dynamic behavior of wind turbine systems is thus in need of attention. The vibration of rotor blades and supporting towers of two wind turbine systems have been measured remotely using IBIS, a microwave interferometer. However the frequency of the rotor blade can be analyzed only if the microwave measurements are taken as the wind turbine is parked and secured. Time-frequency analyses such as continuous wavelet transform and reassigned spectrograms are applied to the displacement signals obtained. A frequency of 0.44Hz exists in both turbines B and C at various operating conditions. Possible links between dynamic characteristics and structural integrity of wind turbine –tower systems is discussed.

Gearbox is one of the most vulnerable subsystems in wind turbines. Its healthy status significantly affects the efficiency and function of the entire system. Vibration based fault diagnosis methods are prevalently applied nowadays. However, vibration signals are always contaminated by noise that comes from data acquisition errors, structure geometric errors, operation errors, etc. As a result, it is difficult to identify potential gear failures directly from vibration signals, especially for the early stage faults. This paper utilizes synchronous averaging technique in time-frequency domain to remove the non-synchronous noise and enhance the fault related time-frequency features. The enhanced time-frequency information is further employed in gear fault classification and identification through feature extraction algorithms including Kernel Principal Component Analysis (KPCA), Multilinear Principal Component Analysis (MPCA), and Locally Linear Embedding (LLE). Results show that the LLE approach is the most effective to classify and identify different gear faults.

Portland Cement Concrete plays a vital part of protecting structural rebars or steels when high-temperature fire incidents occur, that induces loss of evaporate water, dehydration of CH, and deconstruction of C-S-H. The objective of the study was to assess fire-damaged concrete in conjunction with nondestructive evaluation methods of acoustic emission, visual inspections, and X-ray computed tomography. The experimental program was to mix an Ordinary Portland Cement concrete firstly. Concrete cylinders with twenty-day moisture cure were treated in a furnace with 400 and 600°C for one hour. After temperature is cooled down, the concrete cylinders were brought to air or moisture re-curing for ten days. Due to the incident of the furnace, acoustic emission associated with splitting tensile strength test was not able to continue. Future efforts are planned to resume this unfinished task. However, two proposed tasks were executed and completed, namely visual inspections and voids analysis on segments obtained from X-ray CT facility. Results of visual inspections on cross-sectional and cylindrical length of specimens showed that both aggregates and cement pastes turned to pink or red at 600°C. More surface cracks were generated at 600°C than that at 400°C. On the other hand, voids analysis indicated that not many cracks were generated and voids were remedied at 400°C. However, a clear tendency was found that remedy by moisture curing may heal up to 2% voids of the concrete cylinder that was previously subject to 600°C of high temperature conditioning.

Ultrasonic guided waves are now routinely used in non-destructive evaluation. In plate-like structures, three fundamental modes can propagate, namely A₀, S₀ and SH₀. Most of the guided wave literature has thus far focused on the use of A0 and/or S0 because these modes are easy to generate in plate-like structures using standard piezoceramic transducers. Yet, at low frequency, A₀ and S₀ are dispersive. The consequence of dispersion is that signal processing becomes complex for long propagation distances. SH₀, on the other hand, has the particularity of being the only non-dispersive guided wave mode. Omnidirectional transduction of SH₀ requires a rotational surface stress which cannot be easily generated using standard piezoceramic transducers. This paper presents a transducer concept based on piezoceramic patches assembled to form a discretized circle. The external diameter of the discretized circle was chosen to be half the SH₀ wavelength at the desired centre frequency. Finite element simulations using the Comsol Multiphysics environment showed that in a 1.6 mm aluminium plate the modal selectivity of the transducer was more than 25 dB at 100 kHz. A full transducer was built for experimental validation. The experimental modal selectivity was in the region of 20 dB.

The University of California at San Diego (UCSD), under a Federal Railroad Administration (FRA) Office of Research and Development (R&D) grant, is developing a system for high-speed and non-contact rail defect detection. A prototype using an ultrasonic air-coupled guided wave signal generation and air-coupled signal detection, paired with a real-time statistical analysis algorithm, has been realized. This system requires a specialized filtering approach based on electrical impedance matching due to the inherently poor signal-to-noise ratio of air-coupled ultrasonic measurements in rail steel. Various aspects of the prototype have been designed with the aid of numerical analyses. In particular, simulations of ultrasonic guided wave propagation in rails have been performed using a Local Interaction Simulation Approach (LISA) algorithm. The system’s operating parameters were selected based on Receiver Operating Characteristic (ROC) curves, which provide a quantitative manner to evaluate different detection performances based on the trade-off between detection rate and false positive rate. The prototype based on this technology was tested in October 2014 at the Transportation Technology Center (TTC) in Pueblo, Colorado, and again in November 2015 after incorporating changes based on lessons learned. Results from the 2015 field test are discussed in this paper.

Corrosion of steel reinforcing bars (rebars) is the primary cause for the deterioration of reinforced concrete structures. Traditional corrosion monitoring methods such as half-cell potential and linear polarization resistance can only detect the presence of corrosion but cannot quantify it. This study presents an experimental investigation of quantifying degree of corrosion of steel rebar inside cement mortar specimens using ultrasonic testing (UT). A UT device with two 54 kHz transducers was used to measure ultrasonic pulse velocity (UPV) of cement mortar, uncorroded and corroded reinforced cement mortar specimens, utilizing the direct transmission method. The results obtained from the study show that UPV decreases linearly with increase in degree of corrosion and corrosion-induced cracks (surface cracks). With respect to quantifying the degree of corrosion, a model was developed by simultaneously fitting UPV and surface crack width measurements to a two-parameter linear model. The proposed model can be used for predicting the degree of corrosion of steel rebar embedded in cement mortar under similar conditions used in this study up to 3.03%. Furthermore, the modeling approach can be applied to corroded reinforced concrete specimens with additional modification. The findings from this study show that UT has the potential of quantifying the degree of corrosion inside reinforced cement mortar specimens.

Fiber optic acoustic generators have generated a lot of interest due to its great potential in many applications including nondestructive tests. This paper reports four acoustic generation configurations. All the configurations are based on gold nanoparticles/polydimethylsiloxane (PDMS) composites. Since gold nanoparticles have high absorption efficiency to optical energy and PDMS has a high coefficient of thermal expansion, the composites can transfer optical energy to ultrasonic waves with high conversion efficiency. The strength and bandwidth of ultrasonic waves generated by the composites can be changed by different designs and structures of the composites. This paper explores the relation between the structure of fiber optic acoustic generators and the profile of generated ultrasonic waves. Experimental results also demonstrated that four ultrasonic generation configurations have similar features of ultrasonic transmission on a steel plate, which is important for future choices of ultrasonic receivers.

Glass fiber reinforced polymer (GFRP) composites constitute nearly 90% of the global composites market and are extensively used in aerospace, marine, automotive and construction industries. While their advantages of lightweight and superior mechanical properties are well explored, non-destructive evaluation (NDE) techniques that allow for damage/defect detection and assessment of its extent and severity are not fully developed. Some of the conventional NDE techniques for GFRPs include ultrasonics, X-ray, IR thermography, and a variety of optical techniques. Optical methods, specifically measuring the transmission properties (e.g. ballistic optical imaging) of specimens, provide noninvasive, safe, inexpensive, and compact solutions and are commonly used in biomedical applications. In this work, this technique is adapted for rapid NDE of GFRP composites. In its basic form, the system for optical transmission scanning (OTS) consists of a light source (laser diode), a photo detector and a 2D translation stage. The proposed technique provides high-resolution, rapid and non-contact OT (optical transmittance)-scans, and does not require any coupling. The OTS system was used for inspection of pristine and low-velocity impacted (damaged) GFRP samples. The OT-scans were compared with conventional ultrasonic C-scans and showed excellent agreement but with better resolution. Overall, the work presented lays the groundwork for cost-effective, non-contact, and rapid NDE of GFRP composite structures.

Nowadays, the application of glass-fibre composites in light-weight structures is growing. Although mechanical characterizations of those structures are commonly performed in testing, chemical changes of materials under stresses have not yet been well documented. In the present work coupon tests and Hyperspectral Imaging (HSI) have been used to categorise possible chemical changes of glass-fibre reinforced polymers (GFRP) which are currently used in the aircraft industry. HSI is a hybrid technique that combines spectroscopy with imaging. It is able to detect chemical degradation of surfaces and has already been successfully applied in a wide range of fields including astronomy, remote sensing, cultural heritage and medical sciences. GFRP specimens were exposed to two different thermal loading conditions. One thermal loading condition was a continuous thermal exposure at 120°C for 24h, 48 h and 96h, i.e. ageing at a constant temperature. The other thermal loading condition was thermal cycling with three different numbers of cycles (4000, 8000, 12000) and two temperature ranges (0°C to 120°C and -25°C to 95°C). The effects of both conditions were measured using both HSI and interlaminar shear (ILSS) tests. No significant changes of the physical properties of the thermally cycled GFRP specimens were detected using interlaminar shear strength tests and optical microscopy. However, when using HIS, differences of the surface conditions were detected. The results showed that the different thermal loading conditions could be successfully clustered in different colours, using the HSI linear unmixing technique. Each different thermal loading condition showed a different chemical degradation level on its surface which was indicated using different colours.

This paper presents a damage detection and localization technique based on nonlinear elastic waves propagation in a damage composite laminate. The proposed method relies on the time of arrival estimation of the second harmonic nonlinear response obtained with second order phase symmetry analysis filtering and burst excitation. The Akaike Information Criterion approach was used to estimate the arrival times measured by six receiver transducers. Then, a combination of Newton’s method and unconstrained optimization was employed to solve a system of nonlinear equations in order to obtain the material damage coordinates. To validate this methodology, experimental tests were carried out on a damaged composite plate. The results showed that the technique allows calculating the damage position with high accuracy (maximum error ~5 mm).

A two-dimensional (2-D) non-contact areal scan system was developed to image and quantify impact damage in a composite plate using an enhanced zero-lag cross-correlation reverse-time migration (E-CCRTM) technique. The system comprises a single piezoelectric actuator mounted on the composite plate and a laser Doppler vibrometer (LDV) for scanning a region to capture the scattered wavefield in the vicinity of the PZT. The proposed damage imaging technique takes into account the amplitude, phase, geometric spreading, and all of the frequency content of the Lamb waves propagating in the plate; thus, the reflectivity coefficients of the delamination can be calculated and potentially related to damage severity. Comparisons are made in terms of damage imaging quality between 2-D areal scans and linear scans as well as between the proposed and existing imaging conditions. The experimental results show that the 2-D E-CCRTM performs robustly when imaging and quantifying impact damage in large-scale composites using a single PZT actuator with a nearby areal scan using LDV.

This study demonstrates the capability of inductively coupled piezoelectric sensors to monitor the state of health throughout the lifetime of composite structures. A single sensor which generated guided elastic waves was embedded into the stacking sequence of a large glass fiber reinforced plastic plate. The progress of cure was monitored by measuring variations in the amplitude and velocity of the waveforms reflected from the plate’s edges. Baseline subtraction techniques were then implemented to detect barely visible impact damage (BVID) created by a 10 Joule impact, at a distance of 350 mm from the sensor embedded in the cured plate. To investigate the influence of mechanical loading on sensor performance, a single sensor was embedded within a glass fiber panel and subjected to tensile load. The panel was loaded up to a maximum strain of 1%, in increments of 0.1% strain. Guided wave measurements were recorded by the embedded sensor before testing, when the panel was under load, and after testing. The ultrasonic measurements showed a strong dependence on the applied load. Upon removal of the mechanical load the guided wave measurements returned to their original values recorded before testing. The results in this work show that embedded piezoelectric sensors can be used to monitor the state of health throughout the life-cycle of composite parts, even when subjected to relatively large strains. However the influence of load on guided wave measurements has implications for online monitoring using embedded piezoelectric transducers.

Video monitoring of public spaces is becoming increasingly ubiquitous, particularly near essential structures and facilities. During any hazard event that dynamically excites a structure, such as an earthquake or hurricane, proximal video cameras may inadvertently capture the motion time-history of the structure during the event. If this dynamic time-history could be extracted from the repurposed video recording it would become a valuable forensic analysis tool for engineers performing post-disaster structural evaluations. The difficulty is that almost all potential video cameras are not installed to monitor structure motions, leading to camera perspective distortions and other associated challenges. This paper presents a method for extracting structure motions from videos using a combination of computer vision techniques. Images from a video recording are first reprojected into synthetic images that eliminate perspective distortion, using as-built knowledge of a structure for calibration. The motion of the camera itself during an event is also considered. Optical flow, a technique for tracking per-pixel motion, is then applied to these synthetic images to estimate the building motion. The developed method was validated using the experimental records of the NEESHub earthquake database. The results indicate that the technique is capable of estimating structural motions, particularly the frequency content of the response. Further work will evaluate variants and alternatives to the optical flow algorithm, as well as study the impact of video encoding artifacts on motion estimates.

This study focuses on deformability and damage detection of a concrete masonry wall. It employed point-to-point traditional strain gages and full-field measurement technique using digital image correlation (DIC) to investigate the damage and deformability of a partially grouted (PG) reinforced masonry wall. A set of ungrouted and grouted assemblages and full-scale concrete masonry shear wall were constructed and tested under displacement control loading. The wall was constructed according with masonry standards joint committee (MSJC 2013) and tested under constant vertical compression load and horizontal lateral load using quasi-static displacement procedure. The DIC method was used to determine non-uniform strain contours on the assemblages. This method was verified by comparing strains along the selected directions with traditional TML gage results. After a successful comparison, the method was used to investigate the state of damage and deformability of the wall specimen. Panel deformation, crack pattern, displacement at the top, and the base strain of the wall were captured using full-field measurement and results were in a good agreement with traditional strain gages. It is concluded that full-filed measurements using DIC is promising especially when the test specimens experience inelastic deformation and high degree of damage. The ability to characterize and anticipate failure mechanisms of concrete masonry systems by depicting strain distribution, categorizing structural cracks and investigating their effects on the behavior of the wall were also shown using DIC. In addition to monitoring strains across the gage length, the DIC method provided full-field strain behavior of the test specimens and revealed strain hotspots at locations that corresponded to failure.

In this study, an algorithm using image processing techniques is proposed to identify bolt-loosening in bolted connections of steel structures. Its basic concept is to identify rotation angles of nuts from a pictured image, and is mainly consisted of the following 3 steps: (1) taking a picture for a bolt joint, (2) segmenting the images for each nut by image processing techniques, and (3) identifying rotation angle of each nut and detecting bolt-loosening. By using the concept, an algorithm is designed for continuous monitoring and inspection of the bolt connections. As a key imageprocessing technique, Hough transform is used to identify rotation angles of nuts, and then bolt-loosening is detected by comparing the angles before and after bolt-loosening. Then the applicability of the proposed algorithm is evaluated by experimental tests for two lab-scaled models. A bolted joint model which consists of a splice plate and 8 sets of bolts and nuts with 2×4 array is used to simulate inspection of bridge connections, and a model which is consisted of a ring flange and 32 sets of bolt and nut is used to simulate continuous monitoring of bolted connections in wind turbine towers.

As civil infrastructure (i.e. bridges, railways, and tunnels) continues to age; the frequency and need to perform inspection more quickly on a broader scale increases. Traditional inspection and monitoring techniques (e.g., visual inspection, mechanical sounding, rebound hammer, cover meter, electrical potential measurements, ultrasound, and ground penetrating radar) may produce inconsistent results, require lane closure, are labor intensive and time-consuming. Therefore, new structural health monitoring systems must be developed that are automated, highly accurate, minimally invasive, and cost effective. Three-dimensional (3D) digital image correlation (DIC) systems have the merits of extracting full-field strain, deformation, and geometry profiles. These profiles can then be stitched together to generate a complete integrity map of the area of interest. Concurrently, unmanned aerial vehicles (UAVs) have emerged as valuable resources for positioning sensing equipment where it is either difficult to measure or poses a risk to human safety. UAVs have the capability to expedite the optical-based measurement process, offer increased accessibility, and reduce interference with local traffic. Within this work, an autonomous unmanned aerial vehicle in conjunction with 3D DIC was developed for monitoring bridges. The capabilities of the proposed system are demonstrated in both laboratory measurements and data collected from bridges currently in service. Potential measurement influences from platform instability, rotor vibration and positioning inaccuracy are also studied in a controlled environment. The results of these experiments show that the combination of autonomous flight with 3D DIC and other non-contact measurement systems provides a valuable and effective civil inspection platform.

The paper presents the developing of novel form-stable composite phase change material (PCM) by incorporation of paraffin into lightweight aggregate through vacuum impregnation. The macro-encapsulated Paraffin-lightweight aggregate is a chemical compatible, thermal stable and thermal reliable PCM material for thermal energy storage applications in buildings. The 28 days compressive strength of NWAC using PCM-LWA is 33 - 53 MPa, which has an opportunity for structural purpose. Scanning electronic microscopic images indicated the paraffin can be held inside the porous structure of the aggregate. Thermal performance test showed that the cement paste panel with composite PCM can reduce the indoor temperature.

This paper presents a detailed methodology of deploying wireless sensor network in offshore structures for structural health monitoring (SHM). Traditional SHM is carried out by visual inspections and wired systems, which are complicated and requires larger installation space to deploy while decommissioning is a tedious process. Wireless sensor networks can enhance the art of health monitoring with deployment of scalable and dense sensor network, which consumes lesser space and lower power consumption. Proposed methodology is mainly focused to determine the status of serviceability of large floating platforms under environmental loads using wireless sensors. Data acquired by the servers will analyze the data for their exceedance with respect to the threshold values. On failure, SHM architecture will trigger an alarm or an early warning in the form of alert messages to alert the engineer-in-charge on board; emergency response plans can then be subsequently activated, which shall minimize the risk involved apart from mitigating economic losses occurring from the accidents. In the present study, wired and wireless sensors are installed in the experimental model and the structural response, acquired is compared. The wireless system comprises of Raspberry pi board, which is programmed to transmit the acquired data to the server using Wi-Fi adapter. Data is then hosted in the webpage for further post-processing, as desired.

We present a new in-process laser ultrasound inspection technique for additive manufacturing. Ultrasonic energy was introduced to the part by attaching an ultrasonic transducer to the printer build-plate and driving it with a single-tone, harmonic excitation. The full-field response of the part was measured using a scanning laser Doppler vibrometer after each printer layer. For each scan, we analyzed both the local amplitudes and wavenumbers of the response in order to identify defects. For this study, we focused on the detection of delamination between layers in a fused deposition modeling process. Foreign object damage, localized heating damage, and the resulting delamination between layers were detected in using the technique as indicated by increased amplitude and wavenumber responses within the damaged area.

Two methods have been evaluated in order to locate barely visible impact damage (BVID) in a composite stiffener panel. A nonlinear thermosonics technique and a nonlinear laser vibrometer technique were evaluated. Damaged regions were excited using a piezo shaker in both methods. Evaluation of the damaged regions was done by first determining the second and third order nonlinear harmonic response of the damaged regions. This was then used to determine the excitation frequency. By evaluating the presence of nonlinear responses in the output signal it is possible to excite the damaged structure at frequencies that give high heat generation and high displacements at the damaged regions. The results showed that both methods can be used to locate damaged regions, although it was shown that the stiffener impedes the propagation of the exciting wave and that these tests should be carried out in-between stiffeners in order to maximise the excitation and heating of damaged regions. Furthermore, both methods allowed for excitation of damaged regions over a large area.

In recent years, three-dimensional (3D) terrestrial laser scanning technologies with higher precision and higher capability are developing rapidly. The growing maturity of laser scanning has gradually approached the required precision as those have been provided by traditional structural monitoring technologies. Together with widely available fast computation for massive point cloud data processing, 3D laser scanning can serve as an efficient structural monitoring alternative for civil engineering communities. Currently most research efforts have focused on integrating/calculating the measured multi-station point cloud data, as well as modeling/establishing the 3D meshes of the scanned objects. Very little attention has been spent on extracting the information related to health conditions and mechanical states of structures. In this study, an automated numerical approach that integrates various existing algorithms for geometric identification and damage detection of structural elements were established. Specifically, adaptive meshes were employed for classifying the point cloud data of the structural elements, and detecting the associated damages from the calculated eigenvalues in each area of the structural element. Furthermore, kd-tree was used to enhance the searching efficiency of plane fitting which were later used for identifying the boundaries of structural elements. The results of geometric identification were compared with M3C2 algorithm provided by CloudCompare, as well as validated by LVDT measurements of full-scale reinforced concrete beams tested in laboratory. It shows that 3D laser scanning, through the established processing approaches of the point cloud data, can offer a rapid, nondestructive, remote, and accurate solution for geometric identification and damage detection of structural elements.

This paper presents a new laser reflection technique which can identify the near-surface defects in concrete structures bonded with carbon fiber reinforced polymer (CFRP). In this study, a laser beam is used to illuminate the surface of CFRP-concrete panel, and the pattern of the laser reflection is recorded by a high resolution digital camera. Under the laser illumination, the surface of the tested object is heated and expanded. The surface expansion can be identified through observing the expanding reflection pattern. Based on our experimental observation, the defect region exhibits much greater expansion of laser reflection pattern than that in intact region. Results also indicate that both the defect area and the defect depth can influence the change of reflection pattern. In view of the measurement principle of the laser reflection technique, it is expected that the application can be further extended to the areas like CFRP-wood structures, CFRP-masonry structures and CFRP-steel structures.

A multitude of concrete-based structures are typically part of a light water reactor (LWR) plant to provide the foundation, support, shielding, and containment functions. This use has made its long-term performance crucial for the safe operation of commercial nuclear power plants (NPPs). Extending reactor life to 60 years and beyond will likely increase susceptibility and severity of known forms of degradation. While standard Synthetic Aperture Focusing Technique (SAFT) is adequate for many defects with shallow concrete cover, some defects located under deep concrete cover are not easily identified using the standard SAFT. For many defects, particularly defects under deep cover, the use of frequency banded SAFT improves the detectability over standard SAFT. In addition to the improved detectability, the frequency banded SAFT also provides improved scan depth resolution that can be important in determining the suitability of a particular structure to perform its designed safety function. Specially designed and fabricated test specimens can provide realistic flaws that are similar to actual flaws in terms of how they interact with a particular NDE technique. Because conditions in the laboratory are controlled, the number of unknown variables can be decreased, making it possible to focus on specific aspects, investigate them in detail, and gain further information on the capabilities and limitations of each method. To validate the advantages of frequency banded SAFT on thick concrete, a 2.134 m x 2.134 m x 1.016 m concrete test specimen with twenty deliberately embedded defects was fabricated.

Optical inspection is a non-destructive quality monitoring technique to detect defects in manufactured parts. Automating the defect detection, by application of image processing, prevents the presence of human operators making the inspection more reliable, reproducible and faster. In this paper, a background subtraction technique, based on morphological operations, is proposed. The low-computational load associated with the used morphological operations makes this technique more computationally effective than background subtraction techniques such as spline approximation and surface-fitting. The performance of the technique is tested by applying to detect defects in a weld seam with non-uniform intensity distribution where the defects are precisely segmented. The proposed background subtraction technique is generalizable to sheet, surface, or part defect detection in various applications of manufacturing.

In this research, a new method is presented for eliciting the proper features for recognizing and classifying the kinds of the defects by guided ultrasonic waves. After applying suitable preprocessing, the suggested method extracts the base frequency band from the received signals by discrete wavelet transform and discrete Fourier transform. This frequency band can be used as a distinctive feature of ultrasonic signals in different defects. Principal Component Analysis with improving this feature and decreasing extra data managed to improve classification. In this study, ultrasonic test with A0 mode lamb wave is used and is appropriated to reduce the difficulties around the problem. The defects under analysis included corrosion, crack and local thickness reduction. The last defect is caused by electro discharge machining (EDM). The results of the classification by optimized Neural Network depicts that the presented method can differentiate different defects with 95% precision and thus, it is a strong and efficient method. Moreover, comparing the elicited features for corrosion and local thickness reduction and also the results of the two’s classification clarifies that modeling the corrosion procedure by local thickness reduction which was previously common, is not an appropriate method and the signals received from the two defects are different from each other.

It is quite well accepted that frequency domain procedures are suitable for the design and dynamic analysis of wind turbine structures, especially for floating offshore wind turbines, since random wind loads and wave induced motions are most likely simulated in the frequency domain. This paper presents specific applications of an effective frequency domain scheme to the linear analysis of wind turbine structures in which a 1-D spectral element was developed based on the axially-loaded member. The solution schemes are summarized for the spectral analyses of the tower, the blades, and the combined system with selected frequency-dependent coupling effect from foundation-structure interactions. Numerical examples demonstrate that the modal frequencies obtained using spectral-element models are in good agreement with those found in the literature. A 5-element mono-pile model results in less than 0.3% deviation from an existing 160-element model. It is preliminarily concluded that the proposed scheme is relatively efficient in performing quick verification for test data obtained from the on-site vibration measurement using the microwave interferometer.

A recent variant of time reversal imaging is used to detect and characterize a closed crack based on both the fundamental and the second harmonic components of the scattered waves in the presence of Contact Acoustic Nonlinearity at the crack interface. A Finite Element model, which includes unilateral contact with Coulomb friction to account for contact between the crack faces, is used to compute the scattered field resulting from the interaction between incident longitudinal plane waves and the crack. The knowledge of the scattering for multiple incident angles constitutes the input for the imaging algorithm. Good reconstruction of the crack is obtained from both harmonic sources, and second harmonic based images also enables one to identify the location of the second harmonic sources along the crack. This first imaging based on the second harmonic also offers potential baseline free detection of closed cracks.

Lamb wave propagation is at the center of attention of researchers for structural health monitoring of thin walled structures. This is due to the fact that Lamb wave modes are natural modes of wave propagation in these structures with long travel distances and without much attenuation. This brings the prospect of monitoring large structure with few sensors/actuators. However the problem of damage detection and identification is an “inverse problem” where we do not have the luxury to know the exact mathematical model of the system. On top of that the problem is more challenging due to the confounding factors of statistical variation of the material and geometric properties. Typically this problem may also be ill posed. Due to all these complexities the direct solution of the problem of damage detection and identification in SHM is impossible. Therefore an indirect method using the solution of the “forward problem” is popular for solving the “inverse problem”. This requires a fast forward problem solver. Due to the complexities involved with the forward problem of scattering of Lamb waves from damages researchers rely primarily on numerical techniques such as FEM, BEM, etc. But these methods are slow and practically impossible to be used in structural health monitoring. We have developed a fast and accurate analytical forward problem solver for this purpose. This solver, CMEP (complex modes expansion and vector projection), can simulate scattering of Lamb waves from all types of damages in thin walled structures fast and accurately to assist the inverse problem solver.

The paper presents further development in normalized contrast processing used in flash infrared thermography method. Method of computing normalized image or pixel intensity contrast, and normalized temperature contrast are provided. Methods of converting image contrast to temperature contrast and vice versa are provided. Normalized contrast processing in flash thermography is useful in quantitative analysis of flash thermography data including flaw characterization and comparison of experimental results with simulation. Computation of normalized temperature contrast involves use of flash thermography data acquisition set-up with high reflectivity foil and high emissivity tape such that the foil, tape and test object are imaged simultaneously. Methods of assessing other quantitative parameters such as emissivity of object, afterglow heat flux, reflection temperature change and surface temperature during flash thermography are also provided. Temperature imaging and normalized temperature contrast processing provide certain advantages over normalized image contrast processing by reducing effect of reflected energy in images and measurements, therefore providing better quantitative data. Examples of incorporating afterglow heat-flux and reflection temperature evolution in flash thermography simulation are also discussed.

The present work deals with the nondestructive assessment of the metallic materials’ mechanical damage. An innovative Nondestructive Evaluation (NDE) methodology based on two thermographic approaches was developed in order the state of fatigue damage to be assessed. The first approach allows the detection of heat waves generated by the thermomechanical coupling during the fatigue loading (online method). Specifically, both the thermo-elastic and intrinsic dissipated energy was correlated with the mechanical degradation and the remaining fatigue life. The second approach involves the monitoring of the materials’ thermal behavior using a Peltier device for accurate thermal excitation (offline method). The correlation of the thermal behavior and the state of damage was achieved by the determination of the material’s thermal response. The combination of these two approaches enables the rapid and accurate assessment of the cumulative damage.

Harsh service environment degenerates the performance of bridges even leads to catastrophic collapse. Structural temperature has been widely recognized as one of the most negative environmental effects on bridges. The structural responses are deeply affected by the variation and distribution of temperatures on bridges. Therefore, identifying the correlations between them is a significant issue for structural safety assessment. In this study, the relationships between the temperature induced static response and the surrounding weather factors are investigated based on the long-term field measurements of a long-span suspension bridge. The correlations of the meteorological parameters between the bridge filed and the nearby weather station, and the relations of structural static responses to the air temperature, are investigated. The results indicate that relationships of meteorological parameters between nearby weather station and the bridge field can be predicted. The correlation between the static responses and the air temperature and is remarkable with high correlation coefficient. The conclusions are expected to provide reference for the design and evaluation of longspan suspension bridges.

Corrosion is the leading failure mechanism for metallic structures. One of the standard non-destructive techniques to assess the status and predict remaining lifetime and possible failure is based on the excitation with a varying magnetic field and measuring the change of the magnetic field due to eddy currents in the device under test. Since the magnetic field is decaying quickly a large lift-off between the excitation source, magnetic sensors and the test object will reduce the signals considerably. In order to obtain a deep penetration into the test object excitation at low frequency is desirable. In this study an investigation of a high power excitation system in combination with giant magneto resistance (GMR) based sensors was done. GMR sensors have a good sensitivity and are suitable for low frequency eddy current testing due to their low 1/f noise. Finite element analysis was used to evaluate the excitation setup, sensor alignment and positions and study the influence of different parameters of the excitation and sensor setup as well as the device under test. Based on these results a laboratory setup was build and used to study the influence of main measurement parameters.

An active sensing diagnostic system using PZT based smart rebar for SHM of RC structure has been currently under investigation. Previous test results showed that the system could detect the de-bond of concrete from reinforcement, and the diagnostic signals were increased exponentially with the de-bonding size. Previous study also showed that the smart rebar could function well like regular reinforcement to undertake tension stresses. In this study, a smart rebar network has been used to detect the crack damage of concrete based on guided waves. Experimental test has been carried out for the study. In the test, concrete beams with 2 reinforcements have been built. 8 sets of PZT elements were mounted onto the reinforcement bars in an optimized way to form an active sensing diagnostic system. A 90 kHz 5-cycle Hanning-windowed tone burst was used as input. Multiple cracks have been generated on the concrete structures. Through the guided bulk waves propagating in the structures from actuators and sensors mounted from different bars, crack damage could be detected clearly. Cases for both single and multiple cracks were tested. Different crack depths from the surface and different crack numbers have been studied. Test result shows that the amplitude of sensor output signals is deceased linearly with a propagating crack, and is decreased exponentially with increased crack numbers. From the study, the active sensing diagnostic system using PZT based smart rebar network shows a promising way to provide concrete crack damage information through the “talk” among sensors.

In this article we present a wireless sensor network to monitor the structural health of a large-scale highway bridge in Germany. The wireless sensor network consists of several sensor nodes that use wake-up receivers to realize latency free and low-power communication. The sensor nodes are either equipped with very accurate tilt sensor developed by Northrop Grumman LITEF GmbH or with a Novatel OEM615 GNSS receiver. Relay nodes are required to forward measurement data to a base station located on the bridge. The base station is a gateway that transmits the local measurement data to a remote server where it can be further analyzed and processed. Further on, we present an energy harvesting system to supply the energy demanding GNSS sensor nodes to realize long term monitoring.

Soil mechanical properties play the most important role for the structural safety. But soil itself develops with environment as climate, loading and even surrounding biochemical contents which will strongly change the soil mechanical properties and may bring drastic damage to structural foundation. In-time monitoring and estimating on soil mechanical properties is proposed. Two piezoceramic transducers are embedded in predetermined locations: one is used as the actuator and the other is used as a sensor. The active-sensing method is applied to excite a stress wave propagating between the transducers. Variation of the wave velocity along the wave propagation path can be read while the soil properties changing. In this paper, soil specimens with different dry density, moisture content and soil granite ratio are tested to investigate the wave propagation variation through the soil with different properties. A model of shear wave velocity with different soil properties is established. Experimental results demonstrate that piezoelectric response wave may be potentially used to estimate soil physical properties.

The recent constructed structures are featured by the combination of their functions and shapes as well as by their enlarged dimensions, which increase the demand for Structural Health Monitoring technology. Since every structure bears unique dynamic characteristics and is exposed to diverse external forces, various methods are studied to monitor the health of the structure. This study applies the Hilbert-Huang transform, the variance analysis and the edge detection method on the acceleration response of the structure to identify the initiation time of the abnormal behavior in which the structure experiences abnormal vibration. A scaled cable-supported bridge model is fabricated and subjected to cable failure test from which data before and after the occurrence of the abnormal behavior are acquired and compared to validate the proposed anomaly-extraction technique.

Ultrasonic guided waves have rapidly become an effective device in the field of NDT in recent years. Main reason for this is the ability of transmission from one point on the pipe to travel a long distance along it length. These waves are typically used in relatively low frequencies, and as a result, die out in longer periods of time. In this study, by designing and building a system to generate the needed signal for the stimulation of guided waves through using a piezoelectric crystal, these waves were generated and transmitted along a pipe. After propagation, waves were relieved by an ultrasonic probe and were saved by a digital oscilloscope. The received waves were then processed and filtered to eliminate noise and compared with each other. In order to compare the results and study the effective parameters of inspecting ability by these waves, the receiving probe was moved along the length of the pipe and through clanging the number of entering sinusoidal pulses along with altering the frequency signal; the data was recorded in the highest amplitude frequency. By adjusting the frequency within 30-40 KHz range, it would be possible to receive signals at any point in the experiment. Although the received signals weaken by further distance, however; through increase in the number of pulses of inlet signals, the guided waves better stimulate and become stronger at the outlet signal.

Role of air transport in the development and expansion of world trade leading to economic growth of different countries is undeniable. Continuing the world’s trade sustainability without expansion of aerospace is next to impossible. Based on enormous expenses for design, manufacturing and maintenance of different aerospace structures, correct and timely diagnosis of defects in those structures to provide for maximum safety has the highest importance. Amid all this, manufacturers of commercial and even military aircrafts are after production of less expensive, lighter, higher fuel economy and nonetheless, higher safety. As such, two events has prevailed in the aerospace industries: (1) Utilization of composites for the fuselage as well as other airplane parts, (2) using modern manufacturing methods. Arrival of two these points have created the need for upgrading of the present systems as well as innovating newer methods in diagnosing and detection of defects in aerospace structures. Despite applicability of nondestructive testing (NDT) methods in aerospace for decades, due to some limitations in the defect detection’s certainty, particularly for composite material and complex geometries, shadow of doubt has fallen on maintaining complete confidence in using NDT. These days, two principal approach are ahead to tackle the above mentioned problems. First, approach for the short range is the creative and combinational mean to increase the reliability of NDT and for the long run, innovation of new methods on the basis of structural health monitoring (SHM) is in order. This has led to new philosophy in the maintenance area and in some instances; field of design has also been affected by it.

Deterioration of civil infrastructure in America demands routine inspection and maintenance to avoid catastrophic failures from occurring. Among many other non-destructive evaluations (NDE), photogrammetry is an accessible and realistic approach used for non-destructive evaluation (NDE) of a civil infrastructure systems. The objective of this paper is to explore the capabilities of photogrammetry for locating, sizing, and analyzing the remaining capacity of a specimen or system using point cloud data. Geometric interpretations, composed from up to 70 photographs are analyzed as a mesh or point cloud models. In this case study, concrete, which exhibits a large amount of surface texture features, was thoroughly examined. These evaluative techniques discussed were applied to concrete cylinder models as well as portions of civil infrastructure including buildings, retaining walls, and bridge abutments. In this paper, the aim is to demonstrate the basic analytical functionality of photogrammetry, as well as its applicability to in-situ civil infrastructure systems. In concrete specimens defect length and location can be evaluated in a fully defined model (one with the maximum amount of correctly acquired photographs) with less than 2% error. Error was found to be inversely proportional to the number of acceptable photographs acquired, remaining significantly under 10% error for any model with enough data to render. Furthermore, volumetric stress evaluations were applied using a cross sectional evaluation technique to locate the critical area, and determine the severity of damages. Finally, findings and the accuracy of the results are discussed.

Complete structure identification of complicate nonlinear system using extend Kalman filter (EKF) or unscented Kalman filter (UKF) may have the problems of divergence, huge computation and low estimation precision due to the large dimension of the extended state space for the system. In this article, a decentralized identification method of hysteretic system based on the joint EKF and UKF is proposed. The complete structure is divided into linear substructures and nonlinear substructures. The substructures are identified from the top to the bottom. For the linear substructure, EKF is used to identify the extended space including the displacements, velocities, stiffness and damping coefficients of the substructures, using the limited absolute accelerations and the identified interface force above the substructure. Similarly, for the nonlinear substructure, UKF is used to identify the extended space including the displacements, velocities, stiffness, damping coefficients and control parameters for the hysteretic Bouc-Wen model and the force at the interface of substructures. Finally a 10-story shear-type structure with multiple inter-story hysteresis is used for numerical simulation and is identified using the decentralized approach, and the identified results are compared with those using only EKF or UKF for the complete structure identification. The results show that the decentralized approach has the advantage of more stability, relative less computation and higher estimation precision.

Quick seismic damage investigation in earthquake zone is significant to provide guidance for emergency response and rescue after disaster. In this paper, the damage investigation software is developed, which integrates the functions of questionnaire and picture collection for phenomenon register and image acquisition. The software has been updated to online version, all the information collected can be uploaded to the website with their GPS information, and demonstrated on a map. The expert can evaluate the seismic damage by analyzing the photos and recordings collected, which reduce the waste of human and time.

The electromagnetic acoustic Lamb wave, with the advantages of quickly detecting the defect and sensitivity to the defects, is widely used in non-destructive testing of thin sheet. In this paper, the directivity of sound field, Phase velocity, group velocity and particle displacement amplitude of Lamb wave are study based on finite element analysis method. The results show that, for 1mm aluminum, when the excitation frequency 0.64MHz, the displacement amplitude of A0 mode is minimum, and the displacement amplitude S0 mode is largest. Appropriate to increase the displacement amplitude of a mode, while reducing displacement amplitude of another mode, to achieve the excitation of a single mode Lamb wave. It is helpful to the Optimization of transducer parameters, the choice of Lamb wave modes and providing optimal excitation frequency.

A cantilever beam with a breathing crack is studied to detect and evaluate the crack using entropy measures. Closed cracks in engineering structures lead to proportional complexities to their vibration responses due to weak bi-linearity imposed by the crack breathing phenomenon. Entropy is a measure of system complexity and has the potential in quantifying the complexity. The weak bi-linearity in vibration signals can be amplified using wavelet transformation to increase the sensitivity of the measurements. A mathematical model of harmonically excited unit length steel cantilever beam with a breathing crack located near the fixed end is established, and an iterative numerical method is applied to generate accurate time domain dynamic responses. The bi-linearity in time domain signals due to the crack breathing are amplified by wavelet transformation first, and then the complexities due to bi-linearity is quantified using sample entropy to detect the possible crack and estimate the crack depth. It is observed that the method is capable of identifying crack depths even at very early stages of 3% with the increase in the entropy values more than 10% compared with the healthy beam. The current study extends the entropy based damage detection of rotary machines to structural analysis and takes a step further in high-sensitivity structural health monitoring by combining wavelet transformation with entropy calculations. The proposed technique can also be applied to other types of structures, such as plates and shells.

Steel rebar corrosion reduces the integrity and service life of reinforced concrete (RC) structures and causes their gradual and sudden failures. Early stage detection of steel rebar corrosion can improve the efficiency of routine maintenance and prevent sudden failures from happening. In this paper, detecting the presence of surface rust in steel rebars is investigated by the finite element method (FEM) using surface-generated elastic waves. Simulated wave propagation mimics the sensing scheme of a fiber optic acoustic generator mounted on the surface of steel rebars. Formation of surface rust in steel rebars is modeled by changing material's property at local elements. In this paper, various locations of a fiber optic acoustic transducer and a receiver were considered. Megahertz elastic waves were used and different sizes of surface rust were applied. Transient responses of surface displacement and pressure were studied. It is found that surface rust is most detectable when the rust location is between the transducer and the receiver. Displacement response of intact steel rebar is needed in order to obtain background-subtracted response with a better signal-to-noise ratio. When the size of surface rust increases, reduced amplitude in displacement was obtained by the receiver.

Laminated carbon fiber reinforced polymer (CFRP) composite materials are increasingly used in aerospace structures due to their superior mechanical properties and reduced weight. Assessing the health and integrity of these structures requires non-destructive evaluation (NDE) techniques to detect and measure interlaminar delamination and intralaminar matrix cracking damage. The electrical resistance change (ERC) based NDE technique uses the inherent changes in conductive properties of the composite to characterize internal damage. Several works that have explored the ERC technique have been limited to thin cross-ply laminates with simple linear or circular electrode arrangements. This paper investigates a method of optimum selection of electrode configurations for delamination detection in thick cross-ply laminates using ERC. Inverse identification of damage requires numerical optimization of the measured response with a model predicted response. Here, the electrical voltage field in the CFRP composite laminate is calculated using finite element analysis (FEA) models for different specified delamination size and locations, and location of ground and current electrodes. Reducing the number of sensor locations and measurements is needed to reduce hardware requirements, and computational effort needed for inverse identification. This paper explores the use of effective independence (EI) measure originally proposed for sensor location optimization in experimental vibration modal analysis. The EI measure is used for selecting the minimum set of resistance measurements among all possible combinations of selecting a pair of electrodes among the n electrodes. To enable use of EI to ERC required, it is proposed in this research a singular value decomposition SVD to obtain a spectral representation of the resistance measurements in the laminate. The effectiveness of EI measure in eliminating redundant electrode pairs is demonstrated by performing inverse identification of damage using the full set of resistance measurements and the reduced set of measurements. The investigation shows that the EI measure is effective for optimally selecting the electrode pairs needed for resistance measurements in ERC based damage detection.

This paper presents guided waves based damage detection by using a hybrid PZT actuator and optic fiber Bragg grating (FBG) sensors. In the hybrid sensing, a piezoelectric wafer (PZT) is used to generate incident guided waves based on the piezoelectric principle. Meanwhile, multiple fiber Bragg grating sensors (FBG) are adopted as receivers to measure the high-frequency small-strain guided waves base on the full width half maximum (FWHM) principle. If the inspected structure has damage such as hole, crack and notch, the incident guided waves will be reflected or scattered by the damage. Through multiple FBG sensors at different locations, the damage induced waves can be acquired and further processed for damage detection. In this research, two configurations are explored, the rosette and line arrangements of multiple sensors. The sensing and wave source localization on aluminum plate are demonstrated. The results show that wave source can be successfully detected by using both the FBG rosette and the FBG array.

The thermal protection materials for aircraft are usually assembled on the substrate surface by means of adhesion agent. It is very necessary to evaluate the interface bonding quality which has great influence on heat preservation performance. At present, there is still no relatively satisfactory and reliable method for defect detection of cohesive coating. Planar array electrical capacitance tomography (ECT) is a suitable non-invasive imaging technique when there is only limited access to the targeted object. This research aims to investigate the feasibility of using planar array electrical capacitive tomography for bondline defect detection. In this paper, a planar array ECT system is developed consist of a planar array sensor of 12 electrodes, a capacitance acquisition system and image reconstruction software. The sensor development, simulation of sensitivity map, practical application and imaging reconstruction are discussed. A series of specimens of thermal protection material with man-made defects are tested by the proposed planar array ECT system. The experimental results show that the defect in cohesive coating can be effectively detected and the minimum size can be detected is 10mm×10mm.

Mechanical and electromagnetic waves are commonly used in nondestructive testing (NDT) techniques for evaluating the materials and structures in civil engineering industry, due to their good examination of defects inside the matter. However, the individual use of mechanical wave or electromagnetic wave in NDT methods sometimes does not fulfill the satisfactory detection in practice because of the operational inconvenience and low sensitivity. It has been demonstrated that the combination of using both types of waves can achieve a better performance for NDT application and would be the future direction for defect detection, as the advantages of each physical wave are picked out whereas the weaknesses are mitigated. This paper discusses the fundamental mechanisms and the current applications of using mechanical and electromagnetic waves for defect detection, with the goal of providing the physical knowledge and the perspectives of developing the NDT applications with these two types of waves. Typical mechanical-wave-based NDT methods such as acoustic emission, ultrasonic technique, and impact-echo method are reviewed. In addition, NDT methods using electromagnetic wave, which include optical fiber sensing technique, laser speckle interferometry and laser reflection technique are discussed. Advantages and disadvantages of these methods are outlined. In particular, we focus on a recent NDT method called acoustic-laser technique, which utilizes both the mechanical and electromagnetic waves. The basic principles and some important experimental data recorded by the acoustic-laser technique are described and its future development in the field of defect detection in civil infrastructure is presented.

This paper deals with the use of complimentary nondestructive methods for the evaluation of damage in engineering materials. The application of digital image correlation (DIC) to engineering materials is a useful tool for accurate, noncontact strain measurement. DIC is a 2D, full-field optical analysis technique based on gray-value digital images to measure deformation, vibration and strain a vast variety of materials. In addition, this technique can be applied from very small to large testing areas and can be used for various tests such as tensile, torsion and bending under static or dynamic loading. In this study, DIC results are benchmarked with other nondestructive techniques such as acoustic emission for damage localization and fracture mode evaluation, and IR thermography for stress field visualization and assessment. The combined use of these three nondestructive methods enables the characterization and classification of damage in materials and structures.

Fiber reinforced composites have been utilized for a number of different applications, including aircraft, wind turbine, automobile, construction, manufacturing, and many other industries. During the fabrication, machining (waterjet, diamond and band saws) and assembly of these laminate composites, various edge and hole delamination, fiber pullout and other micro and nanocracks can be formed on the composite panels. The present study mainly focuses on the edge grinding and sealing of the machine damaged fiber reinforced composites, such as fiberglass, plain weave carbon fiber and unidirectional carbon fiber. The MTS tensile test results confirmed that the composite coupons from the grinding process usually produced better and consistent mechanical properties compared to the waterjet cut samples only. In addition to these studies, different types of high strength adhesives, such as EPON 828 and Loctite were applied on the edges of the prepared composite coupons and cured under vacuum. The mechanical tests conducted on these coupons indicated that the overall mechanical properties of the composite coupons were further improved. These processes can lower the labor costs on the edge treatment of the composites and useful for different industrial applications of fiber reinforced composites.

Curved surface is widely exist in key parts of energy and power equipment, such as, turbine blade cylinder block and so on. Cycling loading and harsh working condition of enable fatigue cracks appear on the surface. The crack should be found in time to avoid catastrophic damage to the equipment. A flexible 2D array transducer was developed. 2D Phased Array focusing method (2DPA), Mode-Spatial Double Phased focusing method (MSDPF) and the imaging method using the flexible 2D array probe are studied. Experiments using these focusing and imaging method are carried out. Surface crack image is obtained with both 2DPA and MSDPF focusing method. It have been proved that MSDPF can be more adaptable for curved surface and more calculate efficient than 2DPA.