 Using genetic algorithms and finite element methods to detect shaft crack for rotor-bearing systemYongyong He, Dan Guo and Fulei Chu Mathematics and Computers in Simulation (MATCOM), 2001, vol. 57, issue 1, 95-108 Abstract: Shaft crack is a very dangerous and frequent fault in rotating machine, but how to locate and configure it is just an inverse problem and not easy to tackle. In this paper, a genetic algorithms based method for shaft crack detection is proposed and described, which formulates the shaft crack detection as an optimization problem by means of finite element method and utilizes genetic algorithms to search the solution. Using genetic algorithms avoids some of the weaknesses of traditional gradient based analytical search methods including the difficulty in constructing well-defined mathematical models directly from practical inverse problems. The numerical experiments suggest that good predictions of the shaft crack locations and configuration are possible and the proposed method is feasible. The study also indicates that the proposed method has the potential to solve a wide range of inverse identification problems in a systematic and robust way. Keywords: Shaft crack; Inverse problem; Genetic algorithms; Finite element method (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:57:y:2001:i:1:p:95-108 Access Statistics for this article Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier |
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