Optoelectronic Detecting System for Inner Walls of Pipes

摘要

This paper is concerned with a high characteristic image processing and recognition system that is used for inspecting real-time blemishes, streaks and cracks on the inner walls of high accuracy pipes. As a regular detector, the BP neural network is used for extracting features of the image inspected and classifying these images, it takes fully advantage of the function of artificial neural network, such as the information distributed memory, large scale-adapting parallel processing, high fault-tolerant ability and so forth. Besides, an improved BP algorithm is used in the system for training the network, and making the learning procedure of the net converges to the minimum of overall situation at high rate.