The use of strain gauges is foundational to structural health monitoring, allowing infrastructure to continuously observe strain, infer stress, and potentially detect fatigue/fracture cracks. However, traditional strain gauges have drawbacks. In addition to being costly, a single-element strain gauge will only detect strain in a single direction and must be mounted on smooth surfaces to ensure good adhesion. Soft Elastomeric Capacitors (SECs) have been proposed as a low-cost alternative to traditional strain gauges while allowing for a broader range of applications. They are flexible and can be modeled with different dimensions based on the monitored structure. Each SEC consists of three layers; the two outer layers act as electrodes and are made of a styrene-ethylene-butylene-styrene polymer in a matrix with carbon black. The inner (dielectric) layer comprises titanium oxide in a matrix with SEBS. The use of the SECs is not limited by the geometry of the surface being monitored, and it can, therefore, be adhered to a variety of surfaces as its flexibility allows it to conform to the irregularity and complexity of the monitored structure. The change experienced by a structure will correlate directly to the change in capacitance observed across the sensor, which can be used to predict the monitored structure’s state. While SECs have been studied for applications on various materials, experiments have been limited to adhering the sensor to smooth surfaces. However, concrete structures have various surface finishes that are not uniform, often deriving from an architect’s aesthetic desire. This work tests a corrugated SEC through compression tests on concrete samples with different surface finishing to investigate the effect of surface finishing on the SEC-measured strain. Each concrete sample is subjected to loading by a dynamic testing system, and the data collected from the SEC are compared to off-the-shelf resistive strain gauges. The results show that the performance of the cSEC on the different surfaces is not hindered by different concrete finishes, where a high signal-to-noise ratio of 21 dB and low mean absolute error of 22 μϵ is seen on the concrete specimen with a rough concrete surface. The strain metrics and surface effect on SEC performance are discussed.
Electronic assemblies are subjected to damaging impact and shock loadings in various scenarios, including aerospace, automotive, and military applications. In safety-critical situations, the online detection, quantification, and localization of damage within the electronic assembly would enable intelligent systems to take corrective actions to mitigate or circumvent the effects of damage within the electronic assemblies. This preliminary work investigates a reduced-order model-based method for online damage detection, quantification, and localization of printed circuit boards (PCBs). The local eigenvalue modification procedure (LEMP) is used to accelerate the computational processing time of the model, thereby enabling its use in online damage detection during an impact or shock event. The proposed method tracks changes in the model’s state using an error minimization technique in the frequency domain. A baseline state is established by creating and simulating a numerical model that accurately represents a healthy PCB response. Potential reduced-order models with varying stiffness matrices are developed online and compared to the system’s current state. These reduced-order models introduce a single change in stiffness to the system. LEMP calculates the overall change in the system to obtain the new system-level dynamic response. Incorporating LEMP within the frequency-based analysis demonstrates the potential for effective damage detection on PCBs. This work validates the proposed methodology using a rectangular PCB with induced damage. The PCB is modeled pinned at each corner, and its dynamic response is simulated using ABAQUS and processed with the generalized eigenvalue procedure. LEMP is used to update a single change in the system while obtaining a 587 times speed up when compared to the generalized eigenvalue approach. The LEMP algorithm performance and reliability for updating the model state are discussed in the paper.
The surge in demand for high-energy-density lithium-ion batteries has led to the exploration of high-C (high current draw) discharges in various applications. However, these high-C discharges introduce significant challenges related to battery performance and safety. This exploratory study aims to investigate early current interrupt device failure detection mechanisms in 18650 lithium-ion batteries subjected to discharges up to 16C. Our controlled experimental setup induces a 40 amp discharge to a single lithium nickel cobalt aluminum oxide 18650 cell. Employing digital image correlation techniques, the structural changes in the battery are monitored during discharge, pinpointing subtle deformations and strain patterns as potential precursors to failure. This data, coupled with voltage and temperature measurements, offer a more comprehensive understanding of the battery performance under extreme conditions, allowing for future methods to further enhance safety protocols for high-C discharge.
Surface strain sensors, such as linear variable differential transformers, fiber Bragg gratings, and resistive strain gauges, have seen significant use for monitoring concrete infrastructure. However, spatial monitoring of concrete structures using these sensor systems is limited by challenges in the surface coverage provided by a specific sensor or issues related to mounting and maintaining numerous mechanical sensors on the structure. A potential solution to this challenge is the deployment of large-area electronics in the form of a sensing skin to provide complete coverage of a monitored area while being simple to apply and maintain. Along this line of effort, networks constituted of soft elastomeric capacitors have been deployed to monitor strain on steel and composite structures. However, using soft elastomeric capacitors on concrete surfaces has been challenging due to the electrical coupling between the sensors and concrete, which amplifies transduced strain signals obtained from the soft elastomeric capacitors. In this work, the authors investigate the isolation of the soft elastomeric capacitors from the concrete by extending the styrene-block-ethylene-co-butylene-block-styrene matrix of the soft elastomeric capacitors to include a decoupling layer between the electrode and the concrete. Experimental investigations are carried out on concrete specimens for which the soft elastomeric capacitor is adhered to with a thin layer of off-the-shelf epoxy and then loaded on the dynamic testing system to monitor strain provoked on the concrete samples. The results presented here demonstrate the viability of the electrically isolated soft elastomeric capacitors for monitoring strain on concrete structures. Initial comparisons between un-isolated and electrically isolated soft elastomeric capacitors showed that the nominal capacitance of the soft elastomeric capacitor is significantly lowered by adding an isolation layer of SEBS. Furthermore, strain results for the soft elastomeric capacitors are compared to ones from a resistive strain gauge and digital image correlation. The data obtained is significant for modifying soft elastomeric capacitors with the anticipation for future use on concrete structures.
KEYWORDS: Systems modeling, Finite element methods, Data modeling, Performance modeling, Error analysis, Detection and tracking algorithms, Structural dynamics
Real-time model updating for active structures experiencing high-rate dynamic events such as: hypersonic vehicles, active blast mitigation, and ballistic packages, require that continuous changes in the structure’s state be updated on a timescale of 1 ms or less. This requires the development of real-time model updating techniques capable of tracking the structure’s state. The local eigenvalue modification procedure (LEMP) is a structural dynamic modification procedure that converts the computationally intensive global eigenvalue problem, used in modal analysis, into a set of second-order equations that are more readily handled. Implementation of LEMP for tracking a structure’s state results in secular equations that must be solved to obtain the modified eigenvalues of the structure’s state. In this work, the roots of the secular equations are solved iteratively using a divide and conquer approach, leading to faster root convergence. The present study reports on developing a real-time computing module to perform LEMP in the context of real-time model updating with a stringent timing constraint of 1 ms or less. In this preliminary work, LEMP is applied to tracking the condition of a numerical cantilever beam structure, which depicts changes in a structure’s state as a change in the roller position. A discussion of variations in timing results and accuracy are discussed.
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