This analysis demonstrates a new approach to operational stress estimation using vibration measurement and Kalman filter, suggesting improved reliability even in challenging environments.
Traditional methods for estimating operational stress, such as those relying on strain sensors, often encounter significant challenges in terms of installation, measurement accuracy, and reliability, especially in harsh or inaccessible environments. This study investigates the effectiveness of the joint input state estimation algorithm based on Kalman filter (KF), to estimate operational strain from limited output-only vibration measurements, eliminating the need for complete input data. In this study, a simple beam-system has been investigated subjected to sinusoidal loading and a moving vehicle loading. The results demonstrate the method's accuracy and robustness, even when dealing with sparse and noisy vibration data.
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Chowdhury et al. (2025) studied this question.
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