基于神经网络的地铁列车速度传感器自动化诊断

Automatic diagnosis of subway train speed sensor based on neural network

基于列车运行稳定可靠的需求,提高传感器数据检测的准确性以及及时性的目的,采用以径向神经网络为基础依据,进行双通道传感器数据检测的自动化故障诊断方法,构建地铁列车速度传感器自动化诊断系统。以传感器的工作原理为依据设置两组检测通道,其中一组作为备用通道进行信号检测。同时结合径向神经网络构建速度传感器自动诊断系统,经过精确度阈值以及相角对传感器故障进行诊断。通过实际的验证试验可知,传感器自动化诊断系统能够保证较高的精确度,可对地铁列车速度传感器的工作状态进行及时有效的判断。

In order to improve the stability and reliability of train operation and ensure the timely and accurate detection of sensor data,an automatic fault diagnosis system based on radial neural network for dual⁃channel sensor data detection is proposed.Two sets of detection channels are set up according to the working principle of the sensor,and one of them is used as a backup channel for signal detection.At the same time,combined with the radial neural network,an automatic diagnosis system for the speed sensor is constructed,and the sensor fault is diagnosed through the accuracy threshold and phase angle.After actual experiments,the sensor automatic diagnosis system can ensure high accuracy and judge the working status of the subway train speed sensor in a timely and effective manner.