Online condition monitoring of induction motors

Comparison of particle swarm and simulated annealing algorithms for induction motor fault identification

“…[ ] (4) where T s , is the initial temperature value and T is the current temperature value (T is high at the beginning of the process and reduces gradually every time a solution is replaced, mimicking the metal annealing process, hence the name simulated annealing).…”

“…There has also been considerable interest in detecting winding and other machine faults by examination of terminal current waveforms [2] using data gathered under steady-state operating conditions. Such techniques may involve the calculation of quantities such as input power [3] or negative sequence components [4]. Recent trends in condition monitoring include the detection of machine faults using data acquired during speed transients [5] and the estimation of machine parameters [6].…”

An alternative use of power quality information - Load signature studies & applications

“…Over the years, knowledge and capabilities of monitoring and analyzing power quality attributes have matured and technologies such as sensors and disturbance analyzers are also made available to both electric utilities and industrial users. In the meantime, using the same electrical "signatures" to monitor individual equipment as means of health monitoring [11], fault detection [12]- [14] and usage tracking [15] are also emerging.…”

Early detection of stator voltage imbalance in three-phase induction motors

“…To this end, several online fault monitoring techniques of varying complexity have been developed and deployed. Examples of the relatively simple techniques include Negative Sequence Detectors [1], Kappa Transforms [2], Voltage Mismatch Detectors [3,4]. More advanced techniques of pattern classification have also been used, for example, Mechanical Vibration Monitoring [5], Signal Spectral Analysis [6], and Fuzzy Logic and Neural Networks [7,8].…”