Robust Diagnosis Method Based on Parameter Estimation for an Interturn Short-Circuit Fault in Multipole PMSM under High-Speed Operation

This paper proposes a diagnosis method for a multipole permanent magnet synchronous motor (PMSM) under an interturn short circuit fault. Previous works in this area have suffered from the uncertainties of the PMSM parameters, which can lead to misdiagnosis. The proposed method estimates the q-axis inductance (Lq) of the faulty PMSM to solve this problem. The proposed method also estimates the faulty phase and the value of G, which serves as an index of the severity of the fault. The q-axis current is used to estimate the faulty phase, the values of G and Lq. For this reason, two open-loop observers and an optimization method based on a particle-swarm are implemented. The q-axis current of a healthy PMSM is estimated by the open-loop observer with the parameters of a healthy PMSM. The Lq estimation significantly compensates for the estimation errors in high-speed operation. The experimental results demonstrate that the proposed method can estimate the faulty phase, G, and Lq besides exhibiting robustness against parameter uncertainties

Interturn Short Fault Diagnosis in a PMSM by Voltage and Current Residual Analysis With the Faulty Winding Model

As interturn short fault (ISF) in a permanent-magnet synchronous machine (PMSM) degrades its energy efficiency and may cause other problems, accurate fault diagnosis for the PMSMs is necessary. In this paper, we present a method that uses voltage and current residual components to diagnose the phase and the severity of the ISF in PMSMs. A faulty-winding model (FWM) is introduced to analyze the fault; the model describes a relationship between the voltage decrease of the faulty winding to the characteristics of the fault such as a fault resistance and a fault turn ratio. Based on the model, we suggest a fault index (FI) that shows the severity of the ISF. As the ISF induces residual components to both voltage and current, the proposed method utilized those components with the FWM. A least squares (LS) method is used to estimate the FI and to diagnose the ISF of PMSMs. Experimental results demonstrate that the proposed method diagnose the ISF effectively.11sciescopu

Interturn Short Circuit Fault Detection of Permanent Magnet Synchronous Motors Based on Positive- and Negative-Sequence Signatures

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Detection and Classification of Demagnetization and Interturn Short Faults of IPMSMs

We present a method that detects and classifies demagnetization and interturn short faults (ISFs), which degrade the performance of permanent-magnet synchronous machines (PMSMs). Demagnetization and ISF are analyzed using models; we focused on changes of magnitude and angle of currents in the synchronous frame. Those two faults increase the magnitude of the input current compared with normal machines at the same load torque. However, our analysis suggests that demagnetization causes increase in the current angle beta, whereas ISF causes decrease in beta. We exploit this difference in response to classify the fault if one is detected in the PMSM. Experimental studies on interior-type PMSMs verify that demagnetization and ISF can be detected and classified in various operation conditions.113sciescopu

Detection of Pinholes in Steel Slabs Using Gabor Filter Combination and Morphological Features

In this paper, an algorithm for detecting pinholes was proposed. Pinholes are very tiny holes generated in the surfaces of scarfed slabs. To detect various sizes of pinholes, the Gabor filter combination was applied. A new image segmentation method was proposed in pre-processing. To reduce the number of pseudo-defects, dual thresholding method was used. We have increased the performance of classification by adding new morphological features to general texture based features. To evaluate the performance of proposed algorithm, an images obtained in real production line were used.111sciescopu