| 基于方差随机序列的故障诊断方法 |
| |
| 引用本文： | 刘成瑞,傅惠民. 基于方差随机序列的故障诊断方法[J]. 机械强度, 2006, 28(2): 190-195 |
| |
| 作者姓名： | 刘成瑞 傅惠民 |
| |
| 作者单位： | 北京航空航天大学,小样本技术研究中心,北京,100083;北京航空航天大学,小样本技术研究中心,北京,100083 |
| |
| 摘 要： | 研究发现，方差随机序列的样本标准差能很好表征没备性能的稳定状况，由此提出一种新的故障诊断方法，该方法首先给出一种新的故障诊断特征量，然后采用Mahalanobis距离建立相应的判别函数，进而能对谱分析、时频分析等传统方法无法诊断而工程中又大量存在的一类故障模式进行准确分析和判别。
|
| 关 键 词： | 故障诊断 故障模式 故障特征量 样本标准差 Mahalanobis距离判别函数 设备稳定性 |
| 收稿时间： | 2005-09-16 |
| 修稿时间： | 2005-09-162005-11-26 |
FAULT DIAGNOSIS METHOD BASED ON VARIANCE RANDOM SERIES |
| |
| LIU ChengRui,FU HuiMin. FAULT DIAGNOSIS METHOD BASED ON VARIANCE RANDOM SERIES[J]. Journal of Mechanical Strength, 2006, 28(2): 190-195 |
| |
| Authors: | LIU ChengRui FU HuiMin |
| |
| Affiliation: | Research Center of Small Sample Technology, Beijing University of Aeronautics and Astronautics, Beijing 100083, China |
| |
| Abstract: | It is found that the sample standard deviation of variance random series can describe the stabilization of equipment performance. Based on the discovery, a fault diagnosis method is presented. It gives a new fault diagnosis characteristic quantity, and constitutes the Mahalanobis distance function for discriminating the fault equipments. Through application in engineering, it is shown that the proposed method can diagnose a kind of failure mode which the traditional method, such as the spectrum analysis and time-frequency analysis, cannot diagnose. |
| |
| Keywords: | Fault diagnosis Failure mode Fault characteristic quantity Sample standard deviation Mahalanobis dislance discriminate function Stabilization of equipment performance |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
