Design of Quantitative Detection System of Broken Wire for Steel Rope Based on BP Neural Network

In view of the problem of low detection precision existed in traditional quantitative detection system of broken wire for steel rope, the paper proposed a design scheme of quantitative detection system of broken wire for steel rope based on BP neural network. The system uses flux leakage detection and processing circuit to get damage signal of steel rope, and the signal is sampled with equal-space by single-chip microcomputer controlled by encoder. Then the signal is uploaded to industrial computer, and the industrial computer calls Matlab software to train it with BP neural network to get weight matrix and thre shold matrix, then a forward calculation of BP neural network is made by single-chip microcomputer program, so as to realize judgment of broken wire of steel rope. The detection result showed that the recognition rate of broken wire of steel rope detected by the system is 86.9%, which has certain practicality.