Categorisation and pattern recognition methods for damage localisation from vibration measurements

Trendafilova, I. and Heylen, W. (2003) Categorisation and pattern recognition methods for damage localisation from vibration measurements. Mechanical Systems and Signal Processing, 17 (4). pp. 825-836. ISSN 0888-3270 (http://dx.doi.org/10.1006/mssp.2002.1518)

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Abstract

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.

ORCID iDs

Trendafilova, I. ORCID logoORCID: https://orcid.org/0000-0003-1121-7718 and Heylen, W.;
CORE (COnnecting REpositories)