A robust signal processing method for quantitative high-cycle fatigue crack monitoring using soft elastomeric capacitor sensors

Kong, Xiangxiong; Li, Jian; Collins, William; Bennett, Caroline; Laflamme, Simon; Jo, Hongki

doi:10.1117/12.2260364

Cited by 6 publications

(5 citation statements)

References 26 publications

(21 reference statements)

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“…As the crack forms and propagates, these metrics degrade, which can be attributed to the assumptions made in the electromechanical model yielding unmodeled kinematics and smaller signal-to-noise (SNR) ratio under smaller actuation levels (smaller MTS-derived strain). The observed decrease of SNR and crack detection sensitivity of LAE under smaller strain levels have been reported in other researches [54].…”

Section: Crack Monitoring Algorithmsupporting

confidence: 85%

Investigation of textured sensing skin for monitoring fatigue cracks on fillet welds

Liu¹,

Laflamme²,

Li³

et al. 2022

Meas. Sci. Technol.

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Load-induced fatigue cracking in welds is a critical safety concern for steel transportation infrastructure, and the automation of their detection using commercial sensing technologies remains challenging due to the randomness in crack initiation and propagation. The authors have previously proposed a corrugated soft elastomeric capacitor (cSEC), which is a flexible and ultra-compliant thin-film strain gauge that transduces strain into a measurable change in capacitance. The cSEC technology has been successfully demonstrated for measuring bending strain as well as angular rotation in a folded configuration. This study builds on prior discoveries to characterize the sensor’s capability at monitoring fatigue cracks in corner welds, for which the sensor needs to be installed in a folded configuration. A crack monitoring algorithm is developed to fuse the cSEC data into actionable information. Experimental work is conducted on an orthogonal welded connection, mimicking a plate-to-web joint in steel bridges, with cSECs folded over the fillet welds. The sensor’s electromechanical behavior is characterized, and results confirm that the cSEC is capable of fatigue crack detection and quantification. In particular, results show that the cSEC can detect a minimum crack length of 0.48 mm and that its overall sensing performance, including signal linearity, resolution, and accuracy, is adequate under no damage, yet decreases with increasing crack size, likely attributable to the simplification of the electromechanical model and higher noise produced by the loading equipment under smaller applied displacement.

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Section: Crack Monitoring Algorithmsupporting

confidence: 85%

Investigation of textured sensing skin for monitoring fatigue cracks on fillet welds

Liu¹,

Laflamme²,

Li³

et al. 2022

Meas. Sci. Technol.

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“…Previous work [27,30] have proposed and demonstrated a crack detection and monitoring algorithm by extracting a crack-sensitive feature, termed the crack growth index (CGI), from the A c c e p t e d M a n u s c r i p t 6 SEC's capacitance measurements. This feature extraction method is briefly reviewed here as it serves as the basis for constructing the CGI map to be introduced in Section 2.4.…”

Section: Crack Growth Indexmentioning

confidence: 99%

Sensing distortion-induced fatigue cracks in steel bridges with capacitive skin sensor arrays

Kong

Collins

et al. 2018

Smart Mater. Struct.

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Distortion-induced fatigue cracks represent the majority of fatigue cracks in steel bridges in the United States. Currently, bridge owners, such as the state departments of transportation (DOTs), rely on human inspection to detect, monitor, and quantify these cracks so that appropriate repairs can be applied before cracks reach critical sizes. However, visual inspections are costly, labor intensive, and may be prone to error due to inconsistent skills among bridge inspectors. In this study, we represent a novel strain-based approach for sensing distortion-induced fatigue cracks in steel bridges using soft elastomeric capacitor (SEC) arrays. Compared with traditional foil strain gauges, the SEC technology is a large-area and flexible skin-type strain sensor that can measure a wide range of strain over a large surface. Previous investigations have verified the suitability of a single SEC for sensing an in-plane fatigue crack in a small-scale steel specimen. In this paper, we further demonstrate the ability of SECs for sensing distortion-induced fatigue cracks. The proposed strategy consists of deploying an array of SECs to cover a large fatigue-susceptible region and establishing a fatigue sensing algorithm by constructing a crack growth index (CGI) map. The effectiveness of the strategy was experimentally validated through fatigue tests of bridge girder to cross-frame connection models with distortion-induced fatigue cracks. Test results verified that by deploying an SEC array, multiple CGIs can be obtained over the fatigue-susceptible region, offering a more comprehensive picture of fatigue damage. Furthermore, by monitoring a series of CGI maps constructed under different fatigue cycles, the fatigue crack growth can be clearly visualized through the intensity change in the CGI maps.

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“…Previously, the authors established a novel SEC-based data processing approach [22,25] to extract fatigue-sensitive features, termed the crack growth index (CGI), from SEC measurements for monitoring fatigue crack growth. The methodology of CGI is briefly reviewed in this subsection, which serves as the fundamental basis of the sensing strategy for distortion-induced fatigue cracks in this study.…”

Section: Crack Growth Indexmentioning

confidence: 99%

Dense capacitive sensor array for monitoring distortion-induced fatigue cracks in steel bridges

Kong

Collins

et al. 2018

Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2018

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Distortion-induced fatigue cracks caused by differential deflections between adjacent girders are common issues for steel girder bridges built prior to the mid-1980s in the United States. Monitoring these fatigue cracks is essential to ensure bridge structural integrity. Despite various level of success of crack monitoring methods over the past decades, monitoring distortion-induced fatigue cracks is still challenging due to the complex structural joint layout and unpredictable crack propagation paths. Previously, the authors proposed soft elastomeric capacitor (SEC), a large-size flexible capacitive strain sensor, for monitoring in-plane fatigue cracks. The crack growth can be robustly identified by extracting the crack growth index (CGI) from the measured capacitance signals. In this study, the SECs are investigated for monitoring distortion-induced fatigue cracks. A dense array of SECs is proposed to monitor a large structural surface with fatigue-susceptible details. The effectiveness of this strategy has been verified through a fatigue test of a large-scale bridge girder to cross-frame connection model. By extracting CGIs from the SEC arrays, distortion-induced fatigue crack growth can be successfully monitored.

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A robust signal processing method for quantitative high-cycle fatigue crack monitoring using soft elastomeric capacitor sensors

Cited by 6 publications

References 26 publications

Investigation of textured sensing skin for monitoring fatigue cracks on fillet welds

Investigation of textured sensing skin for monitoring fatigue cracks on fillet welds

Sensing distortion-induced fatigue cracks in steel bridges with capacitive skin sensor arrays

Dense capacitive sensor array for monitoring distortion-induced fatigue cracks in steel bridges

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