International audience—The main objective of this paper is to detect faults in induction machines using a condition monitoring architecture based on stator current measurements. Two types of fault are considered: bearing and broken rotor bars faults. The proposed architecture is based on high-resolution spectral analysis techniques also known as subspace techniques. These frequency estimation techniques allow to separate frequency components including frequencies close to the fundamental one. These frequencies correspond to fault sensitive frequencies. Once frequencies are estimated, their corresponding amplitudes are obtained by using the Least Squares Estimator (LSE). Then, a fault severity criterion is derived from the amplitude estimates. The proposed methods were tested using experimental stator current signals issued from two induction motors with the considered faults. The experimental results show that the proposed architecture has the ability to efficiently and cost-effectively detect faults and identify their severity

International audienceThis paper investigates a new fault detection method for induction machines diagnosis. The proposed detection method is based on hypothesis testing. The decision is made between two hypotheses: the machine is healthy and the machine is faulty. The generalized likelihood ratio test is used to address this issue with unknown signal and noise parameters. To implement this detector, the unknown parameters are replaced by their estimates. Specifically, four estimations are required, which are model order, frequency, phase, and amplitude estimations. The model order is obtained using the Bayesian information criterion. Total least-squares estimation of signal parameters via rotational invariance techniques is used to estimate frequencies. Then, phases and amplitudes are obtained using the least-squares estimator. The proposed approach performance is assessed using simulation data by plotting the receiver operating characteristic curves. Two faults are considered: bearing and broken rotor bar faults. Experimental tests clearly show the effectiveness of the proposed detector