计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (13): 220-222.DOI: 10.3778/j.issn.1002-8331.2009.13.065

• 工程与应用 • 上一篇    下一篇

7500吨浮吊齿轮箱故障诊断系统的研究

陈勇旗1,2,陈启军1   

  1. 1.同济大学 控制科学与工程系,上海 201804
    2.宁波大学 科学技术学院,浙江 宁波 315211
  • 收稿日期:2008-09-11 修回日期:2008-12-19 出版日期:2009-05-01 发布日期:2009-05-01
  • 通讯作者: 陈勇旗

Fault diagnosis of 7500 ton floating crane gear box based on discrete wavelet tikhonov SVM

CHEN Yong-qi1,2,CHEN Qi-jun1   

  1. 1.Department of Control Science and Engineering,Tongji University,Shanghai 201804,China
    2.College of Science and Technology,Ningbo University,Ningbo,Zhejiang 315211,China
  • Received:2008-09-11 Revised:2008-12-19 Online:2009-05-01 Published:2009-05-01
  • Contact: CHEN Yong-qi

摘要: 针对7500吨浮吊齿轮箱故障诊断问题,将离散小波变换和Tikhonov支持向量机结合建立了一个浮吊齿轮箱故障诊断系统。在输入层对振动信号进行离散小波变换,提取不同频带的能量参数作为故障特征向量,利用这些特征向量进行Tikhonov支持向量机的学习,训练后的Tikhonov支持向量机诊断浮吊齿轮箱故障。实验结果表明,离散小波Tikhonov支持向量机具有很强的故障识别性能和鲁棒性,诊断精度优于常规的BP网络方法。

关键词: Tikhonov支持向量机, 离散小波, 浮吊齿轮箱, 故障诊断

Abstract: Discrete wavelet Tikhonov support vector machines(SVM) is presented to solve the problem of fault diagnosis for 7500 ton floating crane gear box,which combines discrete wavelet transform and Tikhonov support vector machines.Vibration signal is processed by discrete wavelet transform at the input layer and the detail energy parameters are obtained as fault character vectors.Tikhonov support vector machines is trained according to these character vectors.The trained Tikhonov support vector machines diagnoses the fault.This method is successfully used to diagnose the fault of 7500 Ton Floating Crane Gear Box.Experiment result proves that the fault recognition rate of the method is better than the regular BP network.

Key words: tikhonov support vector machines, discrete wavelet transform, floating crane gear box, fault diagnosis