Squirrel Cage Induction Motors (SCIMs) are major workhorse of Indian Railways. Continuous online condition monitoring of the SCIMs like Traction Motor (TM) are essential to prevent unnecessary stoppage time in case of a complete failure. Before a complete failure, the TMs generally develop incipient or weak faults. Weak faults have minute influence on the motor performance but eventually leads to complete failure of the motor. If these weak faults are identified at the earliest then, a scheduled maintenance can be planned which will prevent any unplanned stoppage. The signals used for SCIM fault detection are motor current, voltage, vibration, temperature, voltage induced in search coil, etc. The most popular fault detection technology is based on Motor Current Signature Analysis (MCSA). MCSA based online and onboard TM condition monitoring system can be very useful for Indian railways to reduce the cost of operation and unplanned delay by shifting from unnecessary scheduled maintenance to condition-based maintenance of TM and other auxiliary SCIMs.
Bearing fault detection using motor current signal analysis based on wavelet packet decomposition and Hilbert envelope