This paper proposes a diagnosis method that exploits the information delivered by external flux sensors placed in the vicinity of rotating electrical machines, in order to detect a stator interturn short circuit. This fault induces a dissymmetry in the external magnetic field that can be measured by the sensors. Sensitive harmonics are extracted from the signals delivered by a pair of sensors placed at 180° from each other around the machine, and data obtained for several sensor positions are analyzed by fusion techniques using the belief function theory. The diagnosis method is applied on induction and synchronous machines with artificial stator faults. It will be shown that one can obtain high probability to detect the fault using the proposed fusion technique: on various series of measurements, the proposed approach has obtained a 90% detection rate on a considered machine.

As one of the most promising techniques, magnetic flux-based condition monitoring of electrical machines has gained significant traction in the past decade. One of the key enabling factor is the advancements in sensor technologies to measure both the airgap magnetic flux and stray magnetic flux around the motors with high accuracy. This study presents a comprehensive review of advances in flux sensors and the recent trends in magnetic flux based diagnostic techniques for various faults and electrical machines. In this context, various magnetic sensor technologies suitable for measuring both the airgap flux and the stray magnetic flux are introduced. Each of the sensor technologies are discussed exhaustively including their working principles and applications in electrical machine fault diagnostics. In the following sections, various flux based diagnostic techniques are discussed for different types of common faults in various AC machines. Finally, the future trends are discussed briefly under the light of several applications and their impact.

This paper presents a statistical methodology for detection of inter-turn short circuit fault in asynchronous and synchronous machines. This methodology uses a correlation coefficient obtained from external magnetic field measured in the machine vicinity. It is a noninvasive method which follows up the signals of two external flux sensors located symmetrically around the machine axis (180° spatially shifted). The principle is based on the calculation of the Pearson correlation coefficient between two signals delivered by two sensors S1 and S2 when the machine operates at different load conditions, which allows us to detect incipient faults in electrical induction and synchronous machines with a high probability of detection. Experimental tests are realized using two specific rewound machines to create inter-turn short circuit faults with different severity levels.

This study presents an analytical and experimental method for detecting internal turn-to-turn short circuits both in the rotor or in the stator in salient pole synchronous generator machines (SSGM) connected to local power grid. Two main measurements are proposed to confirm or discard these electric faults: external magnetic field and external housing vibrations (EHV). In the event of a short-circuit winding fault, a correlation between external magnetic field and EHV is done to reinforce the diagnosis. Furthermore, the electric power injection dependence is analyzed and a noninvasive technique is proposed to determine the state of the SSGM whatever its load. Thus, it is shown that only noninvasive and online equipment can be used to diagnose SSGM. A diagnostic tool has been developed to show the viability of an operative wireless monitoring system on a 76-MW SSGM in an industrial environment.

This paper presents an analytical approach to estimate the magnitude of a flux density component at a point located outside an AC machine. The study uses the concept of attenuation coefficients which are determined using several hypotheses. The developments consider the different media according to they are flowed by eddy currents or not. Then, the calculations are performed in each medium.