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Shock and Vibration
Volume 2016, Article ID 8726781, 8 pages
Research Article

The Contact State Monitoring for Seal End Faces Based on Acoustic Emission Detection

1School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China
2Sichuan Sunny Seal Co. Ltd, Chengdu 610041, China

Received 19 July 2015; Revised 20 October 2015; Accepted 21 October 2015

Academic Editor: Peng Chen

Copyright © 2016 Xiaohui Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Monitoring the contact state of seal end faces would help the early warning of the seal failure. In the acoustic emission (AE) detection for mechanical seal, the main difficulty is to reduce the background noise and to classify the dispersed features. To solve these problems and achieve higher detection rates, a new approach based on genetic particle filter with autoregression (AR-GPF) and hypersphere support vector machine (HSSVM) is presented. First, AR model is used to build the dynamic state space (DSS) of the AE signal, and GPF is used for signal filtering. Then, multiple features are extracted, and a classification model based on HSSVM is constructed for state recognition. In this approach, AR-GPF is an excellent time-domain method for noise reduction, and HSSVM has advantage on those dispersed features. Finally experimental data shows that the proposed method can effectively detect the contact state of the seal end faces and has higher accuracy rates than some other existing methods.