This paper presents a novel large-area strain sensing technology for monitoring fatigue cracks in steel bridges. The technology is based on a soft elastomeric capacitor (SEC), which serves as a flexible and large-area strain gauge. Previous experiments have verified the SEC's capability to monitor low-cycle fatigue cracks experiencing large plastic deformation and large crack opening. Here an investigation into further extending the SEC's capability for long-term monitoring of fatigue cracks in steel bridges subject to traffic loading, which experience smaller crack openings. It is proposed that the peak-to-peak amplitude (pk-pk amplitude) of the sensor's capacitance measurement as the indicator of crack growth to achieve robustness against capacitance drift during long-term monitoring. Then a robust crack monitoring algorithm is developed to reliably identify the level of pk-pk amplitudes through frequency analysis, from which a crack growth index (CGI) is obtained for monitoring fatigue crack growth under various loading conditions. To generate representative fatigue cracks in a laboratory, loading protocols were designed based on constant ranges of stress intensity to limit plastic deformations at the crack tip. A series of small-scale fatigue tests were performed under the designed loading protocols with various stress intensity ratios. Test results under the realistic fatigue crack conditions demonstrated the proposed crack monitoring algorithm can generate robust CGIs which are positively correlated with crack lengths and independent from loading conditions.

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.

A large area electronics in the form of a soft elastomeric capacitor (SEC) has shown great promise as a strain sensor for fatigue crack monitoring in steel structures. The SEC sensors are inexpensive, easy to fabricate, highly stretchable, and mechanically robust. It is a highly scalable technology, capable of monitoring deformations on mesoscale systems. Preliminary experiments verified the SEC sensor's capability in detecting, localizing, and monitoring crack growth in a compact tension specimen. Here, a numerical simulation method is proposed to simulate accurately the sensor's performance under fatigue cracks. Such method would provide a direct link between the SEC's signal and a fatigue crack geometry, extending the SEC's capability to dense network applications on mesoscale structural components. The proposed numerical procedure consists of two parts: 1) a finite element analysis for the target structure to simulate crack growth based on an element deletion method; 2) an algorithm to compute the sensor's capacitance response using the FE analysis results. The proposed simulation method is validated based on test data from a compact tension specimen. Results from the numerical simulation shows good agreement with SEC's response from the laboratory tests as a function of the crack size. Using these findings, a parametric study is performed to investigate how the SEC would perform under different geometries. Results from the parametric study can be used to optimize the design of a dense sensor network of SECs for fatigue crack detection and localization.

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The authors have previously proposed corrugated soft elastomeric capacitors (cSEC) to create ultra compliant scalable strain gauges. The cSEC technology has been successfully demonstrated in engineering and biomechanical applications for in-plane strain measurements. This study extends work on the cSEC to evaluate its performance at measuring angular rotation when installed folded at the junction of two plates. The objective is to characterize the sensor’s electromechanical behavior anticipating applications to the monitoring of welded connections in steel components. To do so, an electromechanical model that maps the cSEC signal to bending strain induced by angular rotation is derived and adjusted using a validated finite element model. Given the difficulty in mapping strain measurements to rotation, an algorithm termed angular rotation index (ARI) is formulated to link measurements to angular rotation directly. Experimental work is conducted on a hollow structural section (HSS) steel specimen equipped with cSECs subjected to compression to generate angular rotations at the corners within the cross-section. Results confirm that the cSEC is capable of tracking angular rotation-induced bending strain linearly, however with accuracy levels significantly lower than found over flat configurations. Nevertheless, measurements were mapped to angular rotations using the ARI, and it was found that the ARI mapped linearly to the angle of rotation, with an accuracy of 0.416∘.