Fault diagnosis method for rotation machine by using nonlinear correlation between sound and vibration

2017 Fiscal Year Final Research Report

• Project/Area Number: 24760322
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Measurement engineering
• Research Institution: Prefectural University of Hiroshima
• Principal Investigator: Hisako Orimoto (益池寿子) 県立広島大学, 経営情報学部, 准教授 (80533207)
• Project Period (FY): 2013-02-01 – 2018-03-31
• Keywords: 異常診断 / 音と振動 / 相関情報 / 確率論 / 信号処理 / ベイズ推定

Outline of Final Research Achievements

The purpose is to derive a method which can easily, quickly and accurately diagnosis machine faults. In this study, the method that can numerically determine faults situation of machine was developed by using correlation information of sound and vibration. More especially, 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. Next, a diagnostic method which can detect the part of machine with fault for the specific multiple faults is proposed by measuring simultaneously the time series data on sound and vibration.
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.

Free Research Field

信号処理