Optimal Sensor Placement via Parameterized Background Data-Weak Method applied to Magnetostatic Problems including Anisotropy

Abstract

The need for electrical machines is growing in a wide range of applications nowadays, such as for energy production, automotive, marine, and medical equipment, etc. In most of these applications, reliability, efficiency, performance and operational safety are always critical issues, which implies that the monitoring and analysis during the operation of the equipment need to be strengthened. In general, more sensors can give higher accuracy for the estimated physical quantity. However, the system cost, complexity, and size of both system and sensor, as well as the electromagnetic interference can eventually limit the sensor placement. Optimization of the number and the location of the sensors in the monitoring system is one key point to improve system performance, as well as reduce system cost. In this work, an optimal sensor placement strategy is proposed for the application of magnetostatic problems, where the anisotropy of the material is considered. Our development is principally based on the parameterized background data-weak (PBDW) method. The feasibility and efficiency of the proposed approach are illustrated by the numerical experiments.