Comparative Multi Domain Vibration Analysis of Dual Sensors for Structural Health Monitoring
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How to Cite

Manivannan, Gowri Shankar, Guruprasath Jeevajothi, Sanjoy Deb, Venkateswara Rao Kolli, Deepika K C., and Santhosh Kumar K B. 2026. “Comparative Multi Domain Vibration Analysis of Dual Sensors for Structural Health Monitoring”. Journal of Trends in Computer Science and Smart Technology 8 (3): 687-702. https://doi.org/10.36548/jtcsst.2026.2026.3.013.

Keywords

Cluster
Sensors
Structural Health Monitoring
Statistical Testing
Vibration Signals

Abstract

Vibration-based Structural Health Monitoring (SHM) is a powerful technique to monitor the health of engineering structures and identify possible anomalies. In this paper, the vibration signal received using HG24HS and HG07U sensors in Python on Google Colab is thoroughly analyzed. The approach combines time-domain, frequency-domain, statistical, and clustering-based techniques to assess how similar sensor responses are and identify possible structural changes. The time-domain and frequency-domain analyses indicate that the signals have similar amplitudes and spectral properties. Statistical testing, T-test and Mann-Whitney U test, show that there is no significant difference in mean and median behavior, whereas the Kolmogorov-Smirnov test demonstrates on the level of distribution that there are slight variations. The analysis of variance indicates that there is a slight difference in the dispersion of vibration energy in the HG07U sensor. The similarity in vibration patterns with a partial overlap is further supported by clustering analysis. Overall, the findings indicate that the system works in stable conditions and there is no strong indication of structural damage, but slight variations can be noticed that can be explained by localized effects or differences in the sensitivity of the sensors.

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