| 轴承故障诊断与故障预测方法 |
| |
| 引用本文： | 张星辉,康建设,刘占军,李志勇.轴承故障诊断与故障预测方法[J].轴承,2011(1):48-52. |
| |
| 作者姓名： | 张星辉 康建设 刘占军 李志勇 |
| |
| 作者单位： | 1. 军械工程学院装备指挥与管理系,石家庄,050003
2. 军械工程学院训练部,石家庄,050003 |
| |
| 摘 要： | 分析了利用HMM进行故障诊断和HHMM进行故障预测的框架,针对传统HHMM推理算法复杂,推理时间长的问题,将HHMM转化为DBN,并应用交叉树推理算法,缩短了推理时间。最后将HMM和HHMM应用于轴承故障诊断和故障预测或剩余寿命预测(RUL),通过试验结果验证了这种方法的有效性。
|
| 关 键 词： | 滚动轴承 故障诊断 故障预测 隐Markov模型 层次隐Markov模型 动态Bayes网络 剩余寿命预测 |
Diagnosis and Prognosis Method for Bearing Fault |
| |
| ZHANG Xing-hui,KANG Jian-she,LIU Zhan-juna,LI Zhi-yong.Diagnosis and Prognosis Method for Bearing Fault[J].Bearing,2011(1):48-52. |
| |
| Authors: | ZHANG Xing-hui KANG Jian-she LIU Zhan-juna LI Zhi-yong |
| |
| Affiliation: | b(a.Department of Equipment Command and Management;b.Department of Training,Ordnance Engineering College,Shijiazhuang 050003,China) |
| |
| Abstract: | A framework for fault diagnosis is presented based on HMM and fault prognosis based on HHMM.Aimed at that the original inference algorithm of HHMM is somewhat complicated and takes long time,the HHMM is transformed into DBN and the junction tree inference algorithm is employed to shorten the inference time.The proposed methods are applied to fault diagnosis and fault prognosis(remaining useful life,RUL) of a rolling bearing.The results show the validity of the methods. |
| |
| Keywords: | rolling bearing fault diagnosis fault prognosis HMM HHMM DBN remaining useful life prediction |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
|
