Development of computer vision for inspection of bolt using convolutional neural network

The inspection of bolt is difficult in conventional quality check procedure. Computer vision inspection is a suitable method to find interchangeability. The aim of the present study is to develop a device to detect defects in the bolt with the help of computer vision technology. Many traditional techniques are used to find the defects in mechanical components using computer vision in Industries. This paper focuses the development of vision system for measurement and inspection of bolt using camera attached with algorithms. This work is mainly built on the self-learning convolutional neural network to implement computer vision technology to detect the defects. The algorithm is built on the C language and tested repeatedly. After that algorithm is impended on the raspberry pi board, and a neutral stick is attached to the raspberry pi model to operate the algorithm. The camera is attached with the raspberry pi model to capture the image, analyze and identify the defects of bolt. (c) 2020 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Mechanical, Electronics and Computer Engineering 2020: Materials Science.