文件名称:12
- 所属分类：
- 人工智能/神经网络/遗传算法
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- 2012-11-26
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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态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
Yin Andong & Yang Zhengmin
School of Mechanical and Automobile Engineering,Hefei University of Technology,Hefei230009
[Abstract] Based on time series analysis and BP neural networks, a fault diagnosis system is built for ve-
hicle transmission gears. By time series analysis and eigenvectors extraction on operation status signals of trans-
mission 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 ef-
fective and feasible.
-Fault Diagnosis of Vehicle Transmission Gear Based on Time
Series Analysis and Neural Networks
Yin Andong & Yang Zhengmin
School of Mechanical and Automobile Engineering,Hefei University of Technology,Hefei230009
[Abstract] Based on time series analysis and BP neural networks, a fault diagnosis system is built for ve-
hicle transmission gears. By time series analysis and eigenvectors extraction on operation status signals of trans-
mission 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 ef-
fective and feasible.
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基于谱熵的齿轮故障诊断方法研究.caj