Smart Structures and Systems

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Real-time online damage localisation using vibration measurements of structures under variable environmental conditions

  • K. Lakshmi (CSIR-Structural Engineering Research Centre, CSIR Campus)
  • Received : 2023.06.20
  • Accepted : 2024.01.29
  • Published : 2024.03.25
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Abstract

Safety and structural integrity of civil structures, like bridges and buildings, can be substantially enhanced by employing appropriate structural health monitoring (SHM) techniques for timely diagnosis of incipient damages. The information gathered from health monitoring of important infrastructure helps in making informed decisions on their maintenance. This ensures smooth, uninterrupted operation of the civil infrastructure and also cuts down the overall maintenance cost. With an early warning system, SHM can protect human life during major structural failures. A real-time online damage localization technique is proposed using only the vibration measurements in this paper. The concept of the 'Degree of Scatter' (DoS) of the vibration measurements is used to generate a spatial profile, and fractal dimension theory is used for damage detection and localization in the proposed two-phase algorithm. Further, it ensures robustness against environmental and operational variability (EoV). The proposed method works only with output-only responses and does not require correlated finite element models. Investigations are carried out to test the presented algorithm, using the synthetic data generated from a simply supported beam, a 25-storey shear building model, and also experimental data obtained from the lab-level experiments on a steel I-beam and a ten-storey framed structure. The investigations suggest that the proposed damage localization algorithm is capable of isolating the influence of the confounding factors associated with EoV while detecting and localizing damage even with noisy measurements.

Keywords

Acknowledgement

The research work reported in this paper is part of the mission mode project, HCP0018, funded by the Council of Scientific and Industrial Research (CSIR), India, during 2018-20. The authors gratefully acknowledge the support of the technical staff of SHM lab, CSIR-SERC, during the experimental work.

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