TY - GEN
T1 - A Review of Fault Diagnosis for Traction Induction Motor
AU - Tian, Yin
AU - Guo, Dingfei
AU - Zhang, Kunting
AU - Jia, Lihao
AU - Qiao, Hong
AU - Tang, Haichuan
N1 - Publisher Copyright:
© 2018 Technical Committee on Control Theory, Chinese Association of Automation.
PY - 2018/10/5
Y1 - 2018/10/5
N2 - With the rapid development of traction motor, the mechanical health monitoring and fault diagnosis field have entered the era of big data. Definite harmonic signals of the line current are located by a popular method known as motor current signature analysis. Different faults of an induction motor such as rotor, stator, bearing, vibration, air gap eccentricity and their different diagnosis techniques are also explored. In fact, the actual fault detection also has a deep development in the artificial intelligence. It is truly evident that the scope of this area is vast. Hence, acknowledging the need for future research, this review paper presents a birds eye view on different types of traction induction faults and their diagnostics schemes.
AB - With the rapid development of traction motor, the mechanical health monitoring and fault diagnosis field have entered the era of big data. Definite harmonic signals of the line current are located by a popular method known as motor current signature analysis. Different faults of an induction motor such as rotor, stator, bearing, vibration, air gap eccentricity and their different diagnosis techniques are also explored. In fact, the actual fault detection also has a deep development in the artificial intelligence. It is truly evident that the scope of this area is vast. Hence, acknowledging the need for future research, this review paper presents a birds eye view on different types of traction induction faults and their diagnostics schemes.
KW - Artificial intelligence
KW - Current analysis
KW - Fault diagnosis
KW - Model-based approach
KW - Traction induction motors
UR - https://www.scopus.com/pages/publications/85056133717
U2 - 10.23919/ChiCC.2018.8484044
DO - 10.23919/ChiCC.2018.8484044
M3 - 会议稿件
AN - SCOPUS:85056133717
T3 - Chinese Control Conference, CCC
SP - 5763
EP - 5768
BT - Proceedings of the 37th Chinese Control Conference, CCC 2018
A2 - Chen, Xin
A2 - Zhao, Qianchuan
PB - IEEE Computer Society
T2 - 37th Chinese Control Conference, CCC 2018
Y2 - 25 July 2018 through 27 July 2018
ER -