Crack detection of a cantilever beam using kohonen network techniques

Sasanka Choudhury^1* and Dayal Parhi R²

¹Asst. Professor, Department of Mechanical Engineering, KMBB College of Engineering & Technology, Khurda

²Professor, Department of Mechanical Engineering, National Institute of Technology, Rourkela

*Corresponding Author’s E-mail: choudhury.sasanka@yahoo.com

Accepted June 2013

Abstract

The issue of crack detection and diagnosis has gained wide spread industrial interest. Crack/damage affects the industrial economic growth. Generally damage in a structural element may occur due to normal operations, accidents, deterioration or severe natural events such as earth quake or storms. Damage can be analyzed through visual inspection or by the method of measuring frequency, mode shape and structural damping. Damage detection by visual inspection is a time consuming method and measuring of mode shape as well as structural deflection is difficult rather than measuring frequency. As Non- destructive method for the detection of crack is favorable as compared to destructive methods. So, our analysis has been made on the basis of non-destructive methods with the consideration of natural frequency. Here the crack is transverse surface crack. In the current analysis, methodologies have been developed for damage detection of a cracked cantilever beam using kohonen network. Theoretical analysis has been carried out to calculate the natural frequency with the consideration of mass and stiffness matrices. The data obtained from theoretical analysis has been fed to kohonen competitive learning network. Kohonen network is nothing but a competitive learning network is used here for the detection of crack depth and location. It is processed through a vector quantization algorithm.

Keywords: Damage; vibration; natural frequency; kohonen network.