Crack Depth and Crack Location Identification using Artificial Neural Network

Abstract

Identification of crack depth and crack location is an area of concern for researchers across the globe. In the present paper, artificial neural network used to identify crack depth and crack location. Finite element model of rotary shaft with two bearing support was generated. A single crack of varying depth (2mm, 4mm and 6mm) was provided to finite element model of a shaft. Crack distance from bearing support was altered (100 mm, 200 mm, 300 mm and 400 mm). Natural frequency of rotor shaftwas obtained using the modal analysis method. Critical speed of shaft models was obtained from Campbell diagram. Thus, natural frequency and critical speed for all variations of cracks depth and crack locations were obtained. Critical speed and natural frequency for known crack location and crack depth wereused to train an artificial neural network. The training of artificial neural network was completed, with the help of artificial neural network crack location, and crack depth was identified accurately.