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NCUEIR > College of Technology > vr > Periodical Articles > Item 987654321/18333

Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/18333

Title:	An Application of a Recursive Kalman Filtering Algorithm in Rotating Machinery Fault Diagnosis
Authors:	Wu, Jian-Da;Huang, Chin-Wei;Huang, R. W.
Contributors:	車輛科技研究所
Keywords:	Fault diagnosis;Order tracking;Adaptive Kalman filter
Date:	2004-06
Issue Date:	2014-04-29T07:26:50Z
Publisher:	Elsevier Ltd
Abstract:	In this paper, an application of adaptive order tracking fault diagnosis technique based on recursive Kalman filtering algorithm is presented. Order tracking fault diagnosis technique is one of the important tools for fault diagnosis of rotating machinery. Conventional methods of order tracking are primarily based on Fourier analysis with reference to shaft speed. In this study, a high-resolution order tracking method with adaptive Kalman filter is used to diagnose the fault in a gear set and damaged engine turbocharger wheel blades. The adaptive Kalman filtering algorithm can overcome the problems encountered in conventional methods. The problem is treated as the tracking of frequency-varying bandpass signals. Ordered amplitudes can be calculated with high resolution after experimental implementation. Experiments are also carried out to evaluate the proposed system in gear-set defect diagnosis and engine turbocharger wheel blades damaged under various conditions. The experimental results indicate that the proposed algorithm is effective in fault diagnosis of both cases.
Relation:	NDT & E International, 37(5): 411-419
Appears in Collections:	[vr] Periodical Articles

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