DocumentCode :
1604845
Title :
Trends in gear fault detection using electrical signature analysis in induction machine-based systems
Author :
Hedayati Kia, S. ; Henao, H. ; Capolino, G.-A.
Author_Institution :
Dept. of Electr. Eng., Univ. of Picardie “Jules Verne", Amiens, France
fYear :
2015
Firstpage :
297
Lastpage :
303
Abstract :
Vibration measurement and analysis have been used as a classical approach for health state assessment of gears in complex electromechanical systems for many years. Recently, several attempts have been performed for the detection of gear tooth localized faults using induction machine electrical signature analysis with promising results. These previous researches were mainly relied on the study of mechanical impacts effects, generated by gear localized faults, on the mechanical torque and consequently on the stator phase currents. This paper aims to investigate these recent advances with particular focus on the induction machine-based drive systems. Both analytical and modeling approaches will be considered which are helpful for a better understanding of observed phenomena and which leads to identifying both reliability and effectiveness of non-invasive methods for gear tooth localized fault detection.
Keywords :
asynchronous machines; fault diagnosis; gears; electrical signature analysis; gear tooth localized fault detection; health state assessment; induction machine electrical signature analysis; induction machine-based drive systems; mechanical torque; stator phase currents; Frequency modulation; Gears; Induction machines; Stators; Torque; Vibration measurement; Vibrations; AC motor protection; Fault diagnosis; Gearbox; Induction machine; Monitoring; Motor Current Signature Analysis; Signal processing; Space vector; Stator current analysis; Vibration measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Machines Design, Control and Diagnosis (WEMDCD), 2015 IEEE Workshop on
Conference_Location :
Torino
Type :
conf
DOI :
10.1109/WEMDCD.2015.7194543
Filename :
7194543
Link To Document :
بازگشت