Vold–Kalman Filtering Order Tracking Based Rotor Demagnetization Detection in PMSM

Zhu, Min; Yang, Bin; Hu, Wenchao; Guo, Feng; Kar, Narayan C.

doi:10.1109/tia.2019.2932692

Cited by 26 publications

(18 citation statements)

References 29 publications

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“…In addition, this method also has other disadvantages. The excessive calculation problem expressed in VKF-OT-based diagnostic studies [16], [28] is also present in Gabor-OT. Gabor-OT needs motor digital speed information as a second signal, as well as motor current signals used for fault diagnosis, and as a result, the amount of data to be used for fault diagnosis increases.…”

Section: Figure 14 Gabor-ot Results For Testmentioning

confidence: 99%

“…As described in [25] OT defines the order spectrum as the normalization of the rotational speed instead of a certain frequency. FFT-based OT [26], Computed OT [27] and Time-Variant DFT-based OT [25], which are classic OT methods, are non-reconstructionbased methods [28]. Therefore, they offer limited possibilities to the FHCT of a signal.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, they offer limited possibilities to the FHCT of a signal. VKF-OT [16], [28], and Gabor-O [29], which are modern OT techniques, are reconstructionbased methods. These methods are capable of reconstructing harmonic orders in their time history and extracting a specified frequency/order component.…”

Section: Introductionmentioning

confidence: 99%

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Diagnosis of Inter-Turn Faults Based on Fault Harmonic Component Tracking in LSPMSMs Working Under Nonstationary Conditions

Doğan

Tetik

2021

IEEE Access

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Inter-turn faults are one of the most important issues in line-start permanent magnet synchronous motors (LSPMSMs). To date, steady-state operating conditions of LSPMSMs have been analyzed in studies focusing on diagnosing this fault. However, no studies have been conducted for nonstationary operating conditions, such as variable speed or variable load conditions, which are common in the industry. This paper presents a novel approach for fault harmonic component (FHC) tracking based on transient-MCSA to diagnose inter-turn faults in an LSPMSM operating under nonstationary conditions. First, the inter-turn failure model of LSPMS was analyzed to show the fault effect on motor current, and the most dominant inter-turn FHC in the order and frequency domains were determined. Then, using Gabor-OT, interturn FHC signals were extracted from motor current signals in the frequency domain and reconstructed in the time domain. Intrinsic mode functions (IMFs) were calculated by decomposing the reconstructed FHC signals (RFHCSs) via ensemble empirical mode decomposition. Using the energies of RFHCSs, calculated based on Gabor coefficients, and the Kullback-Leibler divergences of the selected IMFs, diagnosis of the inter-turn faults and detection of the severity of the faults was performed. The results are in agreement with the results in the literature, thus showing that the proposed method is a successful and useful means for detecting interturn faults in LSPMSMs.

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Section: Figure 14 Gabor-ot Results For Testmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Diagnosis of Inter-Turn Faults Based on Fault Harmonic Component Tracking in LSPMSMs Working Under Nonstationary Conditions

Doğan

Tetik

2021

IEEE Access

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“…Finally, it was used to train the Dynamic Bayesian Network (DBY) for detecting and predicting demagnetization during machine runtime. With this method, the demagnetization fault was detected very well in a wide speed range [28]. Demagnetization diagnosis was attempted by using continuous wavelet transforms (CWT) and gray system theory (GST).…”

Section: Introductionmentioning

confidence: 99%

An Effective Method for Detection of Demagnetization Fault in Axial Flux Coreless PMSG With Texture-Based Analysis

Mi̇naz

Akcan

2021

IEEE Access

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Due to its high power densities and compact dimensions, the axial flux coreless permanent magnet synchronous generator (PMSG) is used in a wide range of areas such as wind turbines and electric vehicles. It is extremely important to detect magnetization faults that occur in these generators. The occurrence of such faults in these machines with a wide range of areas of use affects their operation negatively. In this study, an effective method has been proposed to detect the demagnetization fault occurring in axial flux coreless PMSGs. The relevant method proposes an effective texture analysis-based feature extraction method, which is an original method in contrast to conventional methods used in the literature. It has been revealed that it is a method that can be used instead of conventional methods such as time-frequency analysis, frequency spectrum analysis, and motor current signature analysis (MCSA) methods. Using the finite element method, current and voltage signals were taken from the healthy and axial flux coreless PMSG with 3% and 6% demagnetization fault. Besides, these signals were retaken at different speeds and loads. After the signals were converted into images, using the features obtained from the images with LBP, fault diagnosis processes were carried out with Knn. It was tested both at different fault rates and under different load and speed conditions to test whether the proposed method worked properly. The success rate of this method was observed as 97.16% and 100%. With the proposed method, it has been revealed that the demagnetization fault can be detected in axial flux coreless PMSGs.INDEX TERMS Image texture analysis, demagnetization, fault detection, permanent magnet machines.

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“…At present, the EMA is usually driven by the permanent magnet synchronous motors (PMSMs) [4][5][6]. However, the EMA is inevitable to work in the condition with strong vibration and high temperature, which are easy to cause the demagnetisation of permanent magnets in PMSMs [7,8]. When compared with the PMSM, the switched reluctance motor (SRM) possesses simpler structure, stronger robustness, better heat resistance, and inherent fault tolerance [9,10].…”

Section: Introductionmentioning

confidence: 99%

Modelling of a direct‐driven electromechanical actuation system based on the Lagrange–Maxwell equation

Long

Yang

et al. 2021

IET Electric Power Appl

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This study proposes an integrated non-linear modelling method for an electromechanical actuation system directly driven by the switched reluctance motor (SDEMA). The mathematical model of the SDEMA system is established by energy analysis and calculation according to the proposed method, which omits the complex analysis of force or torque transmission in the cascade modelling method. By using the Lagrange-Maxwell equation and establishing the energy models of non-linear factors that include the friction, backlash, and flexibility, both the electromechanical coupling effects and the nonlinear factors of the SDEMA system are considered simultaneously in the proposed method. To verify the feasibility and effectiveness of the proposed method, three modelling methods of the SDEMA system are comparatively studied through the simulations and experiments. The results of the simulations and experiments indicate that the proposed integrative non-linear model can reflect the dynamic performance of the SDEMA system more accurately.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Vold–Kalman Filtering Order Tracking Based Rotor Demagnetization Detection in PMSM

Cited by 26 publications

References 29 publications

Diagnosis of Inter-Turn Faults Based on Fault Harmonic Component Tracking in LSPMSMs Working Under Nonstationary Conditions

Diagnosis of Inter-Turn Faults Based on Fault Harmonic Component Tracking in LSPMSMs Working Under Nonstationary Conditions

An Effective Method for Detection of Demagnetization Fault in Axial Flux Coreless PMSG With Texture-Based Analysis

Modelling of a direct‐driven electromechanical actuation system based on the Lagrange–Maxwell equation

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