Development of fatigue crack detection system based on machine vision technology

YUN Yan， GAO Hong-li， SHEN Shan-shan
（Key Laboratory of E&M， Ministry of Education & Zhejiang Province， Zhejiang University of Technology，
Hangzhou 310014，China）

Abstract： In order to solve the problems of  low precision，cumbersome operation，poor anti-jamming，hard to be automatically record etc.,existed in traditional metal fatigue crack detection methods，a non-contact online fatigue crack detection system based on virtual instrument and image processing technology was investigated. This method was presented to be used for online measuring the length of the metal fatigue crack and calculating the growth rate of the crack. Through the hardware selection and modular software design，the development platform based on LabVIEW was established，the fatigue crack propagation experiment was tested，the image processing was realized via NI IMAQ Vision. The maximum crack length measuring error is 0.148 mm based on this online detecting method. And the growth rate of the crack can be gotten via the derivation of crack length-time plot. The results show that this is a relatively ideal fatigue crack measuring approach.
Key words： virtual instrument； image processing； atigue crack； online detection