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Investigations on a particle filter algorithm for crack identification in beams from vibration measurements
Author(s) -
Rangaraj R.,
Pokale Bharat,
Banerjee Anuradha,
Gupta Sayan
Publication year - 2015
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.1733
Subject(s) - beam (structure) , vibration , cantilever , parametric statistics , structural engineering , filter (signal processing) , identification (biology) , enhanced data rates for gsm evolution , particle filter , algorithm , materials science , acoustics , computer science , engineering , mathematics , physics , artificial intelligence , statistics , botany , computer vision , biology
Summary This study focuses on crack identification in beams from vibration measurements using principles of dynamic state estimation. The FEM is used to model the beam with cracked‐beam elements that account for the presence of an edge crack under near‐tip elasto‐plastic conditions. The crack size and its location are treated as the variables that are identified using a particle filter algorithm. A parametric study is first carried out with synthetic measurements to numerically analyze the performance of the algorithm. Subsequently, using measurements acquired from physical experiments involving a cantilever beam subjected to arbitrary excitations, the proposed algorithm is used to identify the size and location of crack‐like defects. The proposed method does not require measurements of the undamaged beam, hence, can be used for crack identification in beams for which no earlier measurements are available. Copyright © 2015 John Wiley & Sons, Ltd.