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this paper presents a study of different time and frequency indicators, extracted from vibration signals of a Permanent Magnet Synchronous Machine (PMSM), for fault detection and diagnosis purpose. First, a multi-physical model of the machine, able to generate the vibration displacement under different operating conditions, is simulated. Then, a brief stateof-the-art on the most encountered machine faults, with their electromagnetic and mechanical signatures, is presented. In this study, both rotor eccentricity and Permanent Magnet (PM) demagnetization faults are considered and introduced in the model by changing some of its parameters. After that, time-and frequency-domains signal processing techniques are applied to extract crucial features sets, related to healthy and faulty cases, from vibration signals. The evolution of these indicators with respect to faults degrees is analyzed to select proper criteria for each one, which can be effectively used latter in fault detection and diagnosis applications.

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the aim of this paper is to present an analytical multiphysical model of Permanent Magnet Synchronous Motors (PMSMs) dedicated to fault detection purpose. The electromagnetic aspect is based on the analytical calculation of the Maxwell pressure in the air-gap. An existing mechanical approach is improved to compute natural frequencies of the machine taking into account its different parts. A better agreement has been obtained between analytical results and those issued from a Finite Element Analysis (FEA) applied to two different stator structures. The dynamic displacement signal of the stator is finally estimated in the space-time domain. Different operating modes of the machine can be simulated by changing some model parameters. In this paper, the rotor eccentricity fault is investigated and detected by the analysis of the vibration signal. Therefore, the proposed multiphysical model could provide healthy and faulty characteristics and could be suitably used for fault detection and diagnosis tasks.

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