Ps (t*k) of failure signal" and statistical information Iqp are defined as the standard indices for evaluation of the extraction results. It has been proven by practical field data and application of the inspection and diagnosis robot that the extraction method discussed in this paper is effective for detection of a failure and distinction of it's origin in the diagnosis of machinery." />


Extraction Method of Failure Signal by Genetic Algorithm and the Application to Inspection and Diagnosis Robot

Peng CHEN  Toshio TOYOTA  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E78-A   No.12   pp.1620-1626
Publication Date: 1995/12/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Acoustic Diagnosis)
Category: 
Keyword: 
genetic algorithm,  inspection and diagnosis robot,  noise cancelling,  sound information,  

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Summary: 
In this study, an extraction method of failure sound signal which is strongly contaminated by noise is investigated by genetic algorithm and statistical tests of the frequency domain for the failure diagnosis of machinery. In order to check the extraction accuracy of the failure signal and obtain the optimum extraction of failure signal, the "existing probability Ps (t*k) of failure signal" and statistical information Iqp are defined as the standard indices for evaluation of the extraction results. It has been proven by practical field data and application of the inspection and diagnosis robot that the extraction method discussed in this paper is effective for detection of a failure and distinction of it's origin in the diagnosis of machinery.