A combined method for triplex pump fault diagnosis based on wavelet transform, fuzzy logic and neuro-networks

被引：49
|
作者：
Kong, FS [1 ]
Chen, RH
机构：
[1] Jilin Univ, Dept Mech Sci & Engn, Changchun 130022, Peoples R China
[2] Petr Univ, Dept Mech Sci & Engn, Beijing 102200, Peoples R China
来源：
MECHANICAL SYSTEMS AND SIGNAL PROCESSING | 2004年 / 18卷 / 01期
关键词：
D O I：
10.1016/S0888-3270(03)00049-9
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
A new combined method based on wavelet transformation, fuzzy logic and neuro-networks is proposed for fault diagnosis of a triplex. The failure characteristics of the fluid- and dynamic-end can be divided into wavelet transform in different scales at the same time (in: Jun Zhu et at. (Eds.), Proceedings of an International Conference on Condition Monitoring. National Defense Industry Press, Beijing, 1997, pp. 271-275). Therefore, the characteristic variables can be constructed making use of the coefficients of Edgeworth asymptotic spectrum expansion formula and fuzzified to train the neuro-network to identify the faults of fluid- and dynamic-end of triplex pump in fuzzy domain. Tests indicate that the information of wavelet transformation in scale 2 is related to the meshing state of the gear and the information in scales 4 and 5 is related to the running state of fluid-end. Good agreement between analytical and experimental results has been obtained. (C) 2003 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码：161 / 168
页数：8
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