摘要
本文运用人工神经网络方法实现对滚动轴承故障的自动分类与诊断。文中给出了神经网络诊断系统的框图,电机滚动轴承振动信号经滤波和包络处理之后,采用RNN网络对包络谱数据进行压缩处理,然后利用基于BP算法的前馈网络实现对轴承故障的自动分类和诊断。实验结果表明,这种诊断方法是行之有效的。
The automatic classification and diagnosis of the rolling bearing faults for electrical machines are performed by ANN and the ANN diagnosing system block diagram is given in this paper. The vibration signal of the rolling bearing in motors is processed by the band-pass filter and envelope analysis. The data of the envelope spectrum are compressed by RNN , and then the automatic classification and diagnosis of the rolling bearing faults are realized by MLPs, which is based on BP algorithm. The results of the test show that this approcach of diagnosis is feasible and effective.
出处
《电工电能新技术》
CSCD
北大核心
1996年第4期1-6,共6页
Advanced Technology of Electrical Engineering and Energy
基金
国家攀登计划项目
关键词
神经网络
故障诊断
电机
轴承
neural networks
fault diagnosis
motor rolling bearing