Time‐frequency representations of auditory signatures: Dynamic signal models

1992 ◽  
Vol 92 (4) ◽  
pp. 2362-2362
Author(s):  
Shelley E. Scruggs ◽  
Gregory H. Wakefield
Keyword(s):  
Time Frequency ◽  
Dynamic Signal ◽  
Signal Models

A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

2020 ◽  
pp. 129-139
Author(s):  
Weihai Sun ◽  
Lemei Han
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Detection Method ◽  
Sound Signal ◽  
Practical Significance ◽  
Time Frequency ◽  
Detection Approach ◽  
Machine Fault ◽  
Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

Time-Frequency Analysis of Partial Discharge Phenomena in SF6 gas using Wavelet Transform

1997 ◽  
Vol 117 (3) ◽  
pp. 338-345 ◽  
Author(s):  
Masatake Kawada ◽  
Masakazu Wada ◽  
Zen-Ichiro Kawasaki ◽  
Kenji Matsu-ura ◽  
Makoto Kawasaki
Keyword(s):  
Wavelet Transform ◽  
Frequency Analysis ◽  
Partial Discharge ◽  
Time Frequency Analysis ◽  
Time Frequency

Time-Frequency Channel Parameterization with Application to Multi-Mode Receivers

2009 ◽  
Vol E92-B (12) ◽  
pp. 3717-3725
Author(s):  
Thomas HUNZIKER ◽  
Ziyang JU ◽  
Dirk DAHLHAUS
Keyword(s):  
Frequency Channel ◽  
Time Frequency ◽  
Multi Mode
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