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Proceedings Paper

Structural damage detection using extended Kalman filter combined with statistical process control
Author(s): Chenhao Jin; Shinae Jang; Xiaorong Sun
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Paper Abstract

Traditional modal-based methods, which identify damage based upon changes in vibration characteristics of the structure on a global basis, have received considerable attention in the past decades. However, the effectiveness of the modalbased methods is dependent on the type of damage and the accuracy of the structural model, and these methods may also have difficulties when applied to complex structures. The extended Kalman filter (EKF) algorithm which has the capability to estimate parameters and catch abrupt changes, is currently used in continuous and automatic structural damage detection to overcome disadvantages of traditional methods. Structural parameters are typically slow-changing variables under effects of operational and environmental conditions, thus it would be difficult to observe the structural damage and quantify the damage in real-time with EKF only. In this paper, a Statistical Process Control (SPC) is combined with EFK method in order to overcome this difficulty. Based on historical measurements of damage-sensitive feathers involved in the state-space dynamic models, extended Kalman filter (EKF) algorithm is used to produce real-time estimations of these features as well as standard derivations, which can then be used to form control ranges for SPC to detect any abnormality of the selected features. Moreover, confidence levels of the detection can be adjusted by choosing different times of sigma and number of adjacent out-of-range points. The proposed method is tested using simulated data of a three floors linear building in different damage scenarios, and numerical results demonstrate high damage detection accuracy and light computation of this presented method.

Paper Details

Date Published: 3 April 2015
PDF: 10 pages
Proc. SPIE 9435, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2015, 94352K (3 April 2015); doi: 10.1117/12.2084466
Show Author Affiliations
Chenhao Jin, Univ. of Connecticut (United States)
Shinae Jang, Univ. of Connecticut (United States)
Xiaorong Sun, Univ. of Connecticut (United States)


Published in SPIE Proceedings Vol. 9435:
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2015
Jerome P. Lynch, Editor(s)

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