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.