基于小波—神经网络的故障劣化趋势检测  

The Examining of the Tendency of the Fault based on the Wavelet and the Neural Networs

作　　者：宋文杰[1] 刘伯峰[2] 王平[1] 姜冰[3] 

机构地区：[1]山东省科学院海洋仪器仪表研究所 [2]海军驻青岛造船厂军事代表室 [3]青岛文达通公司,山东青岛266001

出　　处：《职大学报》2006年第2期81-82,共2页Journal of the Staff and Worker’s University

摘　　要：本文以小波-神经网络为研究对象,主要介绍小波—神经网络的基本原理,及基于小波—神经网络的故障劣化趋势检测系统的构造方法,并以用于温度标定的电机的轴承为例进行诊断试验,试验诊断结果与实际情况基本一致,说明该方法适用于故障劣化趋势检测。This thesis maks a study on the wavelet and neural networks.It introd ucs the basic theorise of the wavelet and the neural networks,moreover,this arti cle recommends the structure method of the detection system of the fault develop ment trend.Authors take bearing of the motor as example that is used in the temp erature calibration.The result of the diagnos:s is in agree with the facts,so th is is proved the method is suitable for the test of the tendency deterioration.

关 键 词：电机轴承 劣化趋势 小波 神经网络 

分 类 号：TH17[机械工程—机械制造及自动化]