Entropy-Based Structural Health Monitoring System for Damage Detection in Multi-Bay Three-Dimensional Structures.

Tzu-Kang Lin,Ana Laínez

doi:10.3390/e20010049

Abstract

In this paper, a structural health monitoring (SHM) system based on multi-scale cross-sample entropy (MSCE) is proposed for detecting damage locations in multi-bay three-dimensional structures. The location of damage is evaluated for each bay through MSCE analysis by examining the degree of dissimilarity between the response signals of vertically-adjacent floors. Subsequently, the results are quantified using the damage index (DI). The performance of the proposed SHM system was determined in this study by performing a finite element analysis of a multi-bay seven-story structure. The derived results revealed that the SHM system successfully detected the damaged floors and their respective directions for several cases. The proposed system provides a preliminary assessment of which bay has been more severely affected. Thus, the effectiveness and high potential of the SHM system for locating damage in large and complex structures rapidly and at low cost are demonstrated.

Highlights

Structural health monitoring (SHM) has attracted considerable attention among engineers, because structures are inevitably subject to internal or external factors that affect their service lives
The signals of two vertically-adjacent floors under the same damage condition were processed through Cross-sample entropy” (SampEn) at multiple scales (MSCE) to evaluate the dissimilarity between floors
After a series of optimization searches [23], where different combinations of parameters were considered for the best performance on damage detection accuracy, the parameters required for the calculation of Cross-SampEn, such as the template length m, threshold r and signal length N, were selected as 4, 0.10× the standard deviation (SD) of the time series and 30,000, respectively

Summary

Introduction

Structural health monitoring (SHM) has attracted considerable attention among engineers, because structures are inevitably subject to internal or external factors that affect their service lives. Over the past two decades, signal-processing techniques have mainly been applied in SHM methods to analyze the measured displacement, velocity or acceleration signals of structures to obtain dynamic characteristics such as basic vibration frequency (natural frequency) and damping. These characteristics contribute to the diagnosis of damage, as well as its condition and possible location [1,2]. In 1999, Wahab and De Roeck [3] used the change in dynamic parameters between the undamaged and damaged conditions of -supported and continuous beams to localize damage. Vibration-based SHM algorithms and their application limitations were examined and summarized by Chang et al [5]

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Conclusion