Paper
3 April 2015 Characterization of a soft elastomeric capacitive strain sensor for fatigue crack monitoring
Xiangxiong Kong, Jian Li, Simon Laflamme, Caroline Bennett, Adolfo Matamoros
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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.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiangxiong Kong, Jian Li, Simon Laflamme, Caroline Bennett, and Adolfo Matamoros "Characterization of a soft elastomeric capacitive strain sensor for fatigue crack monitoring", Proc. SPIE 9435, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2015, 94353I (3 April 2015); https://doi.org/10.1117/12.2176631
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Cited by 4 scholarly publications.
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KEYWORDS
Sensors

Capacitance

Bridges

Metals

Calibration

Data acquisition

Data modeling

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