摘要
将BP神经网络技术应用于铁道车辆齿轮箱故障诊断领域,搭建了BP神经网络诊断模型,在此基础上提出了一种改进的BP算法,并将常规诊断方法所提取的典型故障信号作为神经网络的输入数据,用改进的BP神经网络进行仿真测试。测试结果表明,经过改进的BP神经网络诊断系统具有较好的诊断效率和诊断精度,达到了预期的诊断结果。
BP neural networks technology was applied to the fault diagnosis of railway vehicle gearbox, and BP neural networks diagnose model was created. An improved BP algorithm was put forward, and using the typical fault signal extracted from the routine diagnostic methods as input data of the neural network, simulation and testing in terms of the improved BP neural network were carried out. The results showed that the improved BP neural network system had the better performance of fault diagnosis and fault identification, and could achieve the anticipated diagnosis result.
出处
《机车电传动》
北大核心
2014年第1期97-99,102,共4页
Electric Drive for Locomotives
关键词
铁道车辆
齿轮箱
BP神经网络
故障诊断
仿真测试
railway vehicle： gearbox
BP neural network
fault diagnosis
simulation and testing
