The Application of Pattern Recognition Techniques in Fault Diagnosis of Machinery Equipment

Yan Yu-ling; Xu Yin-ge

Volume 12 Issue 8

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Article Navigation > Applied Mathematics and Mechanics > 1991 > 12(8): 697-701

Yan Yu-ling, Xu Yin-ge. The Application of Pattern Recognition Techniques in Fault Diagnosis of Machinery Equipment[J]. Applied Mathematics and Mechanics, 1991, 12(8): 697-701.

Citation:

Yan Yu-ling, Xu Yin-ge. The Application of Pattern Recognition Techniques in Fault Diagnosis of Machinery Equipment[J]. Applied Mathematics and Mechanics, 1991, 12(8): 697-701.

Citation:

Yan Yu-ling, Xu Yin-ge. The Application of Pattern Recognition Techniques in Fault Diagnosis of Machinery Equipment[J]. Applied Mathematics and Mechanics, 1991, 12(8): 697-701.

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The Application of Pattern Recognition Techniques in Fault Diagnosis of Machinery Equipment

Yan Yu-ling¹,
Xu Yin-ge²

1.
Nanjing Aeronautical Institute, Nanjing;
2.
Beijing Jiaoiong Manager College, Beijing

Received Date: 1989-06-10
Publish Date: 1991-08-15

Abstract

Abstract

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.
- pattern recognition,
- condense state information,
- divergence index,
- inter-object distance,
- intra-object distance

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References(4)

References

[1]	Julius,T.Tou,Pattern Recognition Principles,Addison-Wesley Pub.Comp.Inc.,Massachusetts(1974).
[2]	王飞龙,《模式识别基础》,湖北科技出版社(1986)
[3]	Kashyap,R.L.,Optimal feature selection and decision rules in classification problems withtime series,IEEE Trans.Injorm.Theory,IT-24,3(1978),281-288.
[4]	中山大学数学力学系,《概率论与数理统计》(上).人民教育出版社(1980),

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