Time-Frequency Index

2003 ◽  
pp. 719-743
2018 ◽  
Vol 67 (7) ◽  
pp. 6259-6271 ◽  
Author(s):  
Siyao Lu ◽  
Ibrahim A. Hemadeh ◽  
Mohammed El-Hajjar ◽  
Lajos Hanzo

Author(s):  
Weihai Sun ◽  
Lemei Han

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.


1997 ◽  
Vol 117 (3) ◽  
pp. 338-345 ◽  
Author(s):  
Masatake Kawada ◽  
Masakazu Wada ◽  
Zen-Ichiro Kawasaki ◽  
Kenji Matsu-ura ◽  
Makoto Kawasaki

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