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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.
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