Share Email Print

Proceedings Paper

Hybrid approach based on immune algorithm and support vector machine and its application for fault diagnosis of hydraulic pump
Author(s): Huifeng Niu; Wanlu Jiang; Siyuan Liu; Caiyun Dong
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

This paper describes a hybrid fault diagnosis approach that combines the real-valued negative selection(RNS) algorithm and the support vector machine(SVM) and its application for fault diagnosis of hydraulic pump because it is very difficult to gain the fault samples in the fault diagnosis process of hydraulic pump. In this method, the RNS algorithm is used to generate the nonself set as the fault samples, which are used as the input to SVM algorithm for training purpose. The problem of lacking the fault samples is solved by using this new method. It is accomplished to eliminate the noise existing in the measured signals of hydraulic pump and pick up its features using the wavelet analysis method. Finally, the hydraulic pump fault samples are tested by using the hybrid approach. The classification right rate by this method is 90%, so it is valid for the fault diagnosis of Hydraulic Pump.

Paper Details

Date Published: 31 December 2008
PDF: 6 pages
Proc. SPIE 7130, Fourth International Symposium on Precision Mechanical Measurements, 71304X (31 December 2008); doi: 10.1117/12.819737
Show Author Affiliations
Huifeng Niu, Yanshan Univ. (China)
Wanlu Jiang, Yanshan Univ. (China)
Siyuan Liu, Yanshan Univ. (China)
Caiyun Dong, Yanshan Univ. (China)

Published in SPIE Proceedings Vol. 7130:
Fourth International Symposium on Precision Mechanical Measurements
Yetai Fei; Kuang-Chao Fan; Rongsheng Lu, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?