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Vol. 166, Issue 3, March 2014, pp. 12-22

 

Bullet

 

Fault Diagnosis for the Hydraulic System by Using Autoregressive Trispectrum and its Slices
 

Jibin Jiang, Bingsan Chen, Shoujin Zeng

School of Mechanical and Automotive Engineering, Fujian University of Technology, FuZhou, Fujian, 350108, China
Tel.: 86-591-22863245, fax: 86-591-22863232

E-mail: JibinJ@fjut.edu.cn

 

Received: 20 November 2013 /Accepted: 28 January 2014 /Published: 31 March 2014

Digital Sensors and Sensor Sysstems

 

Abstract: This paper addresses the development of a condition monitoring procedure for mechanical parts which involves time series higher-order spectra analysis. Several approaches based on autoregressive (AR) bispectrum, trispectrum and its slices are investigated as data mining techniques in the fault diagnosis of hydraulic control valves. The characteristics of vibration signals obtained from the control valves have been extracted by means of analyzing the 2-dimensional and diagonal slices of bispectrum and trispectrum, with the main goal of detecting a possible working condition including the normal and fault conditions. The experimental analysis shows that there are distinct bump values in the center of the two-dimensional slices of trispectrum space in the fault conditions, on the contrast, the bump values disappear in normal condition. Comparisons have been done between trispectrum and bispectrum. Results show the slices of the trispectrum reveal the corresponding bispectrum and its slices for diagnosing the faults of the hydraulic control valves. The experimental and theoretical results have indicated that trispectrum is a more suitable tool for diagnosing the faults of the hydraulic control valves.

 

Keywords: Time series, Trispectrum, Slices, Fault diagnosis, Hydraulic system.

 

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