Analytic signal space partitioning and symbolic dynamic filtering for degradation monitoring of electric motors - Springer

摘要

This study presents an application of the recently reported theories of analytic signal space partitioning (ASSP) and symbolic dynamic filtering (SDF) to address degradation monitoring in permanent magnet synchronous motors (PMSM). An (experimentally validated) mathematical model of generic PMSM is chosen to monitor degradation/fault events on a simulation test bed; and the estimated parameter of health condition is observed to vary smoothly and monotonically with degradation in magnetization of the PMSM.