Performance evaluation of an entropy-based structural health monitoring system utilizing composite multiscale cross-sample entropy

Tzu-Kang Lin*, Yi Hsiu Chien

*Corresponding author for this work

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

The aim of this study was to develop an entropy-based structural health monitoring system for solving the problem of unstable entropy values observed when multiscale cross-sample entropy (MSCE) is employed to assess damage in real structures. Composite MSCE was utilized to enhance the reliability of entropy values on every scale. Additionally, the first mode of a structure was extracted using ensemble empirical mode decomposition to conduct entropy analysis and evaluate the accuracy of damage assessment. A seven-story model was created to validate the efficiency of the proposed method and the damage index. Subsequently, an experiment was conducted on a seven-story steel benchmark structure including 15 damaged cases to compare the numerical and experimental models. A confusion matrix was applied to classify the results and evaluate the performance over three indices: accuracy, precision, and recall. The results revealed the feasibility of the modified structural health monitoring system and demonstrated its potential in the field of long-term monitoring.

Original languageEnglish
Article number41
JournalEntropy
Volume21
Issue number1
DOIs
StatePublished - 1 Jan 2019

Keywords

  • Composite cross-sample entropy
  • Multi-scale
  • Structural health monitoring

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