Development of expert system knowledge base to on-line diagnosis of rotor electrical faults of induction motors

The paper concerns the development of the Knowledge Base branch related to rotor electrical faults in squirrel cage machines, to be implemented in an Expert System, utilizing current instantaneous values as input data. The Knowledge Base is organized in two levels: in the first level diagnostic indexes for the orientation of the E.S. inferential engine toward the appropriate branch of the fault tree are utilized. The second level includes the deep knowledge with a data set obtained on the basis of a complete faulty machine model. The diagnostic indexes of the first level concern how to distinguish 'faulty' events from the 'healthy' signals due to the unavoidable manufacturing asymmetries. They are pointed out through a simplified model of faulted rotor that needs few machine parameters. This diagnosis may substitute the second level diagnosis if the machine design data, necessary for the second level diagnosis, are not available or if the extensive work needed for the data base construction would be avoided. Some diagnosis examples are reported to describe the sequence of operations of the diagnostic system.