Journal of Mechanical Science and Technology

The Korean Society of Mechanical Engineers (대한기계학회)
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Crack Identification Using Neuro-Fuzzy-Evolutionary Technique

  • Shim, Mun-Bo (Graduate Student, School of Mechanical Engineering, Sungkyunkwan University) ;
  • Suh, Myung-Won (Associate Professor, School of Mechanical Engineering, Sungkyunkwan University)
  • Published : 2002.04.01
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Abstract

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. Toidentifythelocation and depth of a crack in a structure, a method is presented in this paper which uses neuro-fuzzy-evolutionary technique, that is, Adaptive-Network-based Fuzzy Inference System (ANFIS) solved via hybrid learning algorithm (the back-propagation gradient descent and the least-squares method) and Continuous Evolutionary Algorithms (CEAs) solving sir ale objective optimization problems with a continuous function and continuous search space efficiently are unified. With this ANFIS and CEAs, it is possible to formulate the inverse problem. ANFIS is used to obtain the input(the location and depth of a crack) - output(the structural Eigenfrequencies) relation of the structural system. CEAs are used to identify the crack location and depth by minimizing the difference from the measured frequencies. We have tried this new idea on beam structures and the results are promising.

Keywords

References

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