Share Email Print
cover

Proceedings Paper

Characterization of a soft elastomeric capacitive strain sensor for fatigue crack monitoring
Author(s): Xiangxiong Kong; Jian Li; Simon Laflamme; Caroline Bennett; Adolfo Matamoros
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Fatigue cracks have been one of the major factors for the deterioration of steel bridges. In order to maintain structural integrity, monitoring fatigue crack activities such as crack initiation and propagation is critical to prevent catastrophic failure of steel bridges due to the accumulation of fatigue damage. Measuring the strain change under cracking is an effective way of monitoring fatigue cracks. However, traditional strain sensors such as metal foil gauges are not able to capture crack development due to their small size, limited measurement range, and high failure rate under harsh environmental conditions. Recently, a newly developed soft elastomeric capacitive sensor has great promise to overcome these limitations. In this paper, crack detection capability of the capacitive sensor is demonstrated through Finite Element (FE) analysis. A nonlinear FE model of a standard ASTM compact tension specimen is created which is calibrated to experimental data to simulate its response under fatigue loading, with the goal to 1) depict the strain distribution of the specimen under the large area covered by the capacitive sensor due to cracking; 2) characterize the relationship between capacitance change and crack width; 3) quantify the minimum required resolution of data acquisition system for detecting the fatigue cracks. The minimum resolution serves as a basis for the development of a dedicated wireless data acquisition system for the capacitive strain sensor.

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, 94353I (3 April 2015); doi: 10.1117/12.2176631
Show Author Affiliations
Xiangxiong Kong, The Univ. of Kansas (United States)
Jian Li, The Univ. of Kansas (United States)
Simon Laflamme, Iowa State Univ. (United States)
Caroline Bennett, The Univ. of Kansas (United States)
Adolfo Matamoros, The Univ. of Texas at San Antonio (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)

© SPIE. Terms of Use
Back to Top