Inter-turn fault is a serious stator winding short-circuit fault of permanent magnet synchronous machine(PMSM). Once it occurs, it produces a huge short-circuit current that poses a great risk to the safe operation of...Inter-turn fault is a serious stator winding short-circuit fault of permanent magnet synchronous machine(PMSM). Once it occurs, it produces a huge short-circuit current that poses a great risk to the safe operation of PMSM. Thus, an inter-turn short-circuit fault(ITSCF) diagnosis method based on high frequency(HF) voltage residual is proposed in this paper with proper HF signal injection. First, the analytical models of PMSM after the ITSCF are deduced. Based on the model, the voltage residual at low frequency(LF) and HF can be obtained. It is revealed that the HF voltage residual has a stronger ITSCF detection capability compared to the LF voltage residual. To obtain optimal fault signature, a 3-phase symmetrical HF voltage is injected into the machine drive system, and the HF voltage residuals are extracted. The fault indicator is defined as the standard deviation of the 3-phase HF voltage residuals. The effectiveness of the proposed ITSCF diagnosis method is verified by experiments on a triple 3-phase PMSM. It is worth noting that no extra hardware equipment is required to implement the proposed method.展开更多
Health condition monitoring of induction motors is important because of their vital role and wide us in a variety of industries.A stator inter-turn fault(SITF)is considered to be the most common electrical failure acc...Health condition monitoring of induction motors is important because of their vital role and wide us in a variety of industries.A stator inter-turn fault(SITF)is considered to be the most common electrical failure according to statisti-cal studies.In this paper,an algorithm for the detection of an SITF is presented.It is based on one of the blind source separation techniques called principal component analysis(PCA).The proposed algorithm uses PCA to discriminate between the faulty components of motor current signatures and motor voltage signatures from other components.The standard deviation of one of the decomposed vectors is used as a statistical SITF criterion.The proposed criterion is robust to non-fault conditions including voltage quality problems and large mechanical load changes as well as harmonic contaminants in the voltage supply.In addition,with a straightforward and low computational burden in the fault detection process,the proposed method is computationally efficient.To evaluate the performance of the proposed method,large numbers of practical and simulation scenarios are considered,and the results confrm the good performance,high degree of accuracy,and good convergence speed of the proposed method.展开更多
基金supported in part by the Jiangsu Carbon Peak Carbon Neutralization Science and Technology Innovation Special Fund under Grant BE2022032-1National Natural Science Foundation of China under Grant 52277035, Grant 51937006 and Grant 51907028the “SEU Zhishan Young Scholars” Program of Southeast University。
文摘Inter-turn fault is a serious stator winding short-circuit fault of permanent magnet synchronous machine(PMSM). Once it occurs, it produces a huge short-circuit current that poses a great risk to the safe operation of PMSM. Thus, an inter-turn short-circuit fault(ITSCF) diagnosis method based on high frequency(HF) voltage residual is proposed in this paper with proper HF signal injection. First, the analytical models of PMSM after the ITSCF are deduced. Based on the model, the voltage residual at low frequency(LF) and HF can be obtained. It is revealed that the HF voltage residual has a stronger ITSCF detection capability compared to the LF voltage residual. To obtain optimal fault signature, a 3-phase symmetrical HF voltage is injected into the machine drive system, and the HF voltage residuals are extracted. The fault indicator is defined as the standard deviation of the 3-phase HF voltage residuals. The effectiveness of the proposed ITSCF diagnosis method is verified by experiments on a triple 3-phase PMSM. It is worth noting that no extra hardware equipment is required to implement the proposed method.
文摘Health condition monitoring of induction motors is important because of their vital role and wide us in a variety of industries.A stator inter-turn fault(SITF)is considered to be the most common electrical failure according to statisti-cal studies.In this paper,an algorithm for the detection of an SITF is presented.It is based on one of the blind source separation techniques called principal component analysis(PCA).The proposed algorithm uses PCA to discriminate between the faulty components of motor current signatures and motor voltage signatures from other components.The standard deviation of one of the decomposed vectors is used as a statistical SITF criterion.The proposed criterion is robust to non-fault conditions including voltage quality problems and large mechanical load changes as well as harmonic contaminants in the voltage supply.In addition,with a straightforward and low computational burden in the fault detection process,the proposed method is computationally efficient.To evaluate the performance of the proposed method,large numbers of practical and simulation scenarios are considered,and the results confrm the good performance,high degree of accuracy,and good convergence speed of the proposed method.
