Monitoring the structural health of engineering systems is crucial for ensuring their safety and reliability. However, the accuracy of structural health monitoring (SHM) data can be compromised by environmental factors, such as temperature fluctuations, which may mask or distort the actual structural responses. This paper introduces an innovative approach using an Adaptive Bandwidth Filter Algorithm to separate structure responses from monitoring data, particularly focusing on mitigating the impact of temperature effects. The algorithm's adaptability allows for dynamic adjustments, enhancing its effectiveness across a range of environmental conditions. This research addresses the complexities of temperature-induced distortions in structural monitoring data and proposes a solution for improved accuracy in assessing structural health.
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Journal of Biometrics & Biostatistics received 3496 citations as per Google Scholar report