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Motor rotor broken bar is one of the predominant failure modes of squirrel cage induction motors. There are numerous researched methods for identifying rotor bar faults: motor current signature analysis, acoustic noise measurements, vibration monitoring, temperature monitoring, electromagnetic field monitoring, infrared recognition, radio frequency emissions monitoring, etc. The most frequently used method is called the Motor Current Signature Analysis (MCSA). It is based on a signal analysis of the motor current, obtained via a regular current transformer used for motor protection purposes. It is difficult to detect rotor bar failures by looking into the currents waveform-time domain analysis, however impact of rotor broken bars to the stator currents can be determined by analyzing spectrum of frequency distribution in the frequency domain.Many factors affect reliable detection of the motor broken bar; motor load, system frequency and motor speed, construction of the motor etc. A new algorithm takes into account all these factors to adapt to a changing operational condition of the motor. Also, by learning the healthy motor frequency spectrum signature, the detection of a broken rotor bar can be made even more deterministic.The new algorithm was extensively tested on the induction motors with different system and motor conditions-results of this testing are presented. Lessons learned from the field installations are presented as well.I.

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