This paper presents a symbolic dynamic method for health monitoring of permanent magnet synchronous motors (PMSMs), which involves abstraction of a qualitative description from a dynamical system representation of the PMSM. The underlying algorithms rely on state-space embedding of the PMSM's output line current and discretization of the resultant pseudo-state and input spaces. System identification is achieved through inference of the PMSM's dynamical system behavior, and the deviation of the system's output behavior from the nominal expected behavior yields a measure of the estimated fault. A special-purpose test bed has been designed and fabricated for experimental validation of the health monitoring algorithm via controlled accelerated deterioration of magnetization in the PMSM. The performance of the proposed algorithm has been compared with that of a classical motor current signature analysis (MCSA) procedure as well as with a benchmark particle filter for fault detection in PMSMs.
All Science Journal Classification (ASJC) codes
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering