Identification of Crack Location and Depth in a Structure by GMDH- type Neural Networks and ANFIS

Subject Areas : Journal of Simulation and Analysis of Novel Technologies in Mechanical Engineering

منصور درویزه ¹ , نادر نریمانزاده ² , علی ملیحی دیزگاه ³ , مهدی جوادزاده ⁴ , رضا انصاری ⁵

1 - استاد گروه مهندسی مکانیک دانشگاه گیلان
2 - استاد گروه مهندسی مکانیک دانشگاه گیلان
3 - کارشناس ارشد مهندسی مکانیک دانشگاه گیلان.
4 - کارشناس ارشد مهندسی مکانیک دانشگاه گیلان
5 - استادیار گروه مهندسی مکانیک دانشگاه گیلان.

Received: 2015-10-03 Accepted : 2015-10-03 Published : 2008-12-21

Keywords: ANFIS, Natural frequency, Neural Networks, GMDH, SVD,

Abstract :

The Existence of crack in a structure leads to local flexibility and changes the stiffness and dynamic behavior of the structure. The dynamic behavior of the cracked structure depends on the depth and the location of the crack. Hence, the changes in the dynamic behavior in the structure due to the crack can be used for identifying the location and depth of the crack. In this study the first three natural eigenfrequencies of a cantilever beam having a transverse open crack have been computed for 10 different depths and 30 different locations by the finite element method. These natural eigenfrequencies have been used as input data for GMDH-type neural networks and adaptive neuro-fuzzy inference system, ANFIS, for crack location and depth modeling.

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