基于时序-神经网络的车辆变速器齿轮故障诊断

采用时序分析和BP神经网络，建立了基于时序-神经网络的车辆变速器齿轮故障诊断系统。通过对车辆变速器齿轮运行状念特征信号进行时序分析和特征向量提取，并以此作为BP神经网络的输入向量进行网络训练，从而实现变速器齿轮运行状态的识别与故障诊断。该系统应用于LC5T81变速器齿轮的故障诊断中，能够比较准确地识别与诊断出变速器齿轮的跑合运行状态、磨损运行状态和故障运行状态。验证表明该诊断系统有效、可行。

Fault Diagnosis of Vehicle Transmission Gear Based on Time Series Analysis and Neural Networks

Based on time series analysis and BP neural networks, a fault diagnosis system is built for vehicle transmission gears. By time series analysis and eigenvectors extraction on operation status signals of transmission gears, which are taken as inputs for neural network training, the operation status identification and fault diagnosis for transmission gears are realized. In a fault diagnosis on the gears of a real transmission, the system can accurately identify the operation status (running in, worn or fault). The result shows that the system is effective and feasible.