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http://dx.doi.org/10.1243/JMES_JOUR_1978_020_016_02

has been cited by the following article:

• TITLE: Statistical Fault Diagnosis Methods by Using Higher-Order Correlation Information between Sound and Vibration

  AUTHORS: Hisako Orimoto

  KEYWORDS: Statistical Faults Diagnosis, Correlation Information, Sound and Vibration

  JOURNAL NAME: Intelligent Information Management, Vol.8 No.4, July 12, 2016

  ABSTRACT: It is important to specify the occurrence and cause of failure of machines without stopping the machines because of increased use of various complex industrial systems. In this study, two new diagnosis methods based on the correlation information between sound and vibration emitted from the machine are derived. First, a diagnostic method which can detect the part of machine with fault among the assumed several faults is proposed by measuring simultaneously the time series data on sound and vibration. Next, a diagnosis method based on the estimation of the changing information of correlation between sound and vibration is considered by using prior information in only normal situation. The effectiveness of the proposed theory is experimentally confirmed by applying it to the observed data emitted from a rotational machine driven by an electric motor.