Study on fault diagnosis of intelligent wheel speed sensor based on DBSCAN and BP neural network
In view of the problem that the performance test data of the wheel speed sensor is difficult to identify the failure type in industrial production,the wheel speed sensor fault diagnosis method based on DBSCAN and BP neural network is designed.Firstly,according to the working principle of wheel speed sensor and the actual test data,the fault type of wheel number sensor and the corresponding fault data are analyzed.Then,DBSCAN is used to detect the performance test data of the wheel speed sensor,and to train and test the BP neural network,to diagnose and classify the fault types corresponding to the abnormal values,and to compare the fault diagnosis speed and accuracy of BP neural network with GRNN neural network and PNN neural network.The experimental results show that the wheel speed sensor fault type has obvious advantages.The wheel speed sensor fault detection algorithm designed in this paper can accurately extract the fault data from the test data and diagnose it.
wheel speed sensorthermal shock test chambercentralized monitoringsignal filte-ringfunctional applications
万方数据
维普
