Categorisation and pattern recognition methods for damage localisation from vibration measurements

I. Trendafilova, W. Heylen

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)


This study presents a categorisation (classification) approach towards the damage localisation problem from vibration measurements. A stochastic pattern recognition method for solving such problems is introduced. The method suggests the substructuring in order to reduce the possible damage locations to the number of substructures. It utilises the differences in the frequency response functions of the structure in the damaged and the pre-damaged state. As a result, the damaged substructure(s) is (are) detected by classifying all the substructures as members of the two introduced categories - damaged and non-damaged substructures. A finite element model of the structure is used to train the classification system. The method is demonstrated on a test case of a cantilevered beam. It shows rather accurate performance and low error with simulated and noise-contaminated data. The method can be applied independently for locating a damage in a structure, but it can also be combined with a consequent identification (updating) procedure for more precise localisation and quantification of the existing damage. In the latter case, the subsequent localisation and quantification procedure is restricted to the damaged substructure(s), which facilitates the process and makes it less time consuming.
Original languageEnglish
Pages (from-to)825-836
Number of pages11
JournalMechanical Systems and Signal Processing
Issue number4
Publication statusPublished - 2003


  • vibration
  • categorisation
  • pattern recognition
  • mechanical engineering
  • signal processing


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