THE APPLICATION OF PATTERN RECOGNITION TECHNIQUES IN FAULT DIAGNOSIS OF MACHINERY EQUIPMENT  

作　　者：颜玉玲 徐尹格 

机构地区：[1]Nanjing Aeronautical Institute, Nanjing [2]Peking Jiaotong Manager College, Beijing

出　　处：《Applied Mathematics and Mechanics(English Edition)》1991年第8期745-749,共5页应用数学和力学（英文版）

摘　　要：In this paper, the characteristics of vibration signal of machinery in different running conditions are statistically analysed, and some moments of statistical distribution of signals are selected as the eigenvector to condense the state information. Here, we divide the states of machinery into two: 'good' and 'faulty', and the pattern recognition techniques are used to classify the running conditions of machinery. At the end of this paper, the authors present some test data, and from the results obtained, it's verified that the eigenvector selected is reliable and sensible to faults. And the results also show the effectiveness of classification rule.In this paper, the characteristics of vibration signal of machinery in different running conditions are statistically analysed, and some moments of statistical distribution of signals are selected as the eigenvector to condense the state information. Here, we divide the states of machinery into two: 'good' and 'faulty', and the pattern recognition techniques are used to classify the running conditions of machinery. At the end of this paper, the authors present some test data, and from the results obtained, it's verified that the eigenvector selected is reliable and sensible to faults. And the results also show the effectiveness of classification rule.

关 键 词：pattern recognition condense state information divergence index inter-object distance intra-object distance 

分 类 号：O3，O1[理学—力学]