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RESEARCH PAPERS

A Method of Fault Signature Extraction for Improved Diagnosis

[+] Author and Article Information
Hsinyung Chin, Kourosh Danai

Department of Mechanical Engineering, University of Massachusetts, Amherst, MA 01003

J. Dyn. Sys., Meas., Control 113(4), 634-638 (Dec 01, 1991) (5 pages) doi:10.1115/1.2896468 History: Received September 01, 1990; Revised March 01, 1991; Online March 17, 2008

Abstract

Efficient extraction of fault signatures from sensory data is a major concern in fault diagnosis. This paper introduces a self-tuning method of fault signature extraction that enhances fault detection, minimizes false alarms, improves diagnosability, and reduces fault signature variability. The proposed method uses a Flagging Unit to convert the processed measurements to binary vectors, and utilizes nonparametric pattern classification techniques to estimate the fault signatures. The performance of the Flagging Unit, which relies on its adaptation algorithms to optimize its performance based upon a sample batch of measurement-fault vectors, is demonstrated in simulation.

Copyright © 1991 by The American Society of Mechanical Engineers
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