An Integrated Processing Method for Fatigue Damage Identification in a Steel Structure Based on Acoustic Emission Signals

Yubo Zhang, Hongyun Luo, Junrong Li, Jinlong Lyu, Zheng Zhang, Yue Ma

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

This paper presents an integrated processing method that applies principal component analysis (PCA), artificial neural network (ANN), information entropy and information fusion technique to analyze acoustic emission signals for identifying fatigue damage in a steel structure. Firstly, PCA is used to build different data spaces based on the damage patterns. Input information from each sensor is diagnosed locally through ANN in the data space. The output of the ANNs is used for basic probability assignment. Secondly, the first fusion operation adopts Dempster-Shafer (D-S) evidence theory to combine the basic probability assignment value of ANNs in the different data space of a sensor. Finally, the fusion results of each sensor are combined by D-S evidence theory for the second fusion operation. In this paper, information entropy is used to calculate the uncertainty and construct basic probability assignment function. The damage identification method is verified through four-point bending fatigue tests of Q345 steel. Validation results show that the damage identification method can reduce the uncertainty of the system and has a certain extent of fault tolerance. Compared with ANN and ANN combined with information fusion methods, the proposed method shows a higher fatigue damage identification accuracy and is a potential for fatigue damage identification.

Original languageEnglish
Pages (from-to)1784-1791
Number of pages8
JournalJournal of Materials Engineering and Performance
Volume26
Issue number4
DOIs
Publication statusPublished - 2017 Apr 1

Keywords

  • acoustic emission
  • construction
  • damage identification
  • steel

ASJC Scopus subject areas

  • Materials Science(all)
  • Mechanics of Materials
  • Mechanical Engineering

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