Open AccessA model-based method for bearing fault detection using motor current
Author(s) -
Chen Wang,
Min Wang,
Bin Yang,
Kaiyu Song
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1650/3/032130
Subject(s) - fault (geology) , vibration , bearing (navigation) , accelerometer , computer science , current (fluid) , signal (programming language) , fault detection and isolation , signal processing , position (finance) , control theory (sociology) , engineering , control engineering , electronic engineering , actuator , acoustics , artificial intelligence , electrical engineering , physics , digital signal processing , control (management) , finance , seismology , economics , programming language , geology , operating system
Existing bearing fault diagnosis approaches utilize signal processing techniques in combination with vibration measurements. The common vibration measurement method, using accelerometer, has disadvantages such as position-constrains, high costs and external interferences. Meanwhile, the commonly used modelling methods of motor are not able to analyse both mechanic and electromagnetism simultaneously. For detecting the fault-related frequencies in motor current, a mathematical model is developed in this paper based on modified winding function approach (MWFA). The simulation results show that the fault-related characteristic frequencies can be exactly found in the spectrum results of motor current. The proposed method is proven to be feasible.