Online Rotor Fault Diagnosis of Permanent Magnet Synchronous Motors Based on Stator Tooth Flux

Zhang, Chong; Huang, Song; Lei, Jiayin; Wan, Zhongxin; Yang, Yongming

doi:10.1109/tia.2021.3058541

Cited by 38 publications

(11 citation statements)

References 25 publications

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“…These approaches, similar to other embedded-sensor-based approaches, require unique motor designs or motor modifications. A stator tooth flux based online demagnetization detection is discussed in [19]. A convolutional neural network combined with frequency domain motor current signatures are considered in [20] to detect damage to permanent magnets in a PMSMs.…”

Section: Figure 1 Induced Emf Profile Example Under Non-uniform Demag...mentioning

confidence: 99%

Disambiguation of Uniform Demagnetization Fault From Position Sensor Fault in FOC PMSM Applications

Kuruppu

Abeyratne

2022

IEEE Access

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Electrification of higher torque density applications in the transportation sector and robotics sector are primarily met with permanent magnet synchronous machines (PMSMs), attributing to their unique properties. However, wide operating temperatures, field weakening controls, and low-quality magnets, lead to uniform demagnetization of rotor magnets. Demagnetization in torque control applications reduce the effective output torque as the output torque is proportional to rotor flux level. Detection of such rotor demagnetization is essential and only second to few key faults from the system perspective. However, static position sensor offset error (SPSOE) is a fault mode that may mask itself as a demagnetization fault. Though the demagnetization fault is irreversible, the SPSOE is remediable avoiding sustained-severe degradation of system performance. The false positive nature of demagnetization detection and the SPSOE are discussed in detail in the paper, and a disambiguation strategy is proposed and successfully implemented. Simulation and experimental results are presented to validate the effectiveness of the proposed strategy.

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Section: Figure 1 Induced Emf Profile Example Under Non-uniform Demag...mentioning

confidence: 99%

Disambiguation of Uniform Demagnetization Fault From Position Sensor Fault in FOC PMSM Applications

Kuruppu

Abeyratne

2022

IEEE Access

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“…A polar graph formed by field components of induced coil voltages has been proposed to discern types of eccentricity faults for a concentrated-winding PMSM [74]. Spatiotemporal distribution of the amplitudes of the stator tooth fluxes are presented in [75]. In [76], one search coil is wound around the teeth corresponding to an even number of pole pitches to detect the DE fault.…”

Section: Sensor-based Detectionmentioning

confidence: 99%

A Review of Modeling and Diagnostic Techniques for Eccentricity Fault in Electric Machines

Liu

Zhang

et al. 2021

Energies

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Research on the modeling and fault diagnosis of rotor eccentricities has been conducted during the past two decades. A variety of diagnostic theories and methods have been proposed based on different mechanisms, and there are reviews following either one type of electric machines or one type of eccentricity. Nonetheless, the research routes of modeling and diagnosis are common, regardless of machine or eccentricity types. This article tends to review all the possible modeling and diagnostic approaches for all common types of electric machines with eccentricities and provide suggestions on future research roadmap. The paper indicates that a reliable low-cost non-intrusive real-time online visualized diagnostic method is the trend. Observer-based diagnostic strategies are thought promising for the continued research.

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“…A variety of finite element calculation software, such as Ansys, continues to develop as a result of the development of computers. The demagnetization fault model of a motor is generally established by changing the remanence or magnetic coercivity of the materials of the PM [ 22 , 23 ] or the volume of the PM [ 9 ] in software. It has the advantages of mature application and high calculation accuracy, but it demands a lot of computing time and resources, and the number of elements will also affect the accuracy of the results.…”

Section: Introductionmentioning

confidence: 99%

“…In the magnetic equivalent circuit method, the actual non-uniformly distributed magnetic field is regarded as a multi-section average magnetic circuit, and then the calculation is carried out by analogy with the calculation criteria in the electric circuit. The demagnetization fault model of the motor is generally established by changing the magnetomotive force [ 22 , 23 ] or equivalent magnetic flux and reluctance [ 24 ] of the demagnetized PM in the magnetic circuit model. In [ 22 ], by changing the equivalent magnetomotive force of the demagnetized PM, a mathematical model of the tooth flux of the stator teeth within the range of demagnetized magnetic poles can be established to diagnose the number of demagnetized poles and the degree of demagnetization.…”

Section: Introductionmentioning

confidence: 99%

“…The demagnetization fault model of the motor is generally established by changing the magnetomotive force [ 22 , 23 ] or equivalent magnetic flux and reluctance [ 24 ] of the demagnetized PM in the magnetic circuit model. In [ 22 ], by changing the equivalent magnetomotive force of the demagnetized PM, a mathematical model of the tooth flux of the stator teeth within the range of demagnetized magnetic poles can be established to diagnose the number of demagnetized poles and the degree of demagnetization. In [ 24 ], the leakage flux outside the generator with a demagnetization fault was calculated by adjusting the equivalent flux and reluctance corresponding to the demagnetized PM, which was utilized as the basis for fault diagnosis.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analytical Modeling and Analysis of Permanent-Magnet Motor with Demagnetization Fault

Shi

Peng²,

Zhang³

et al. 2022

Sensors

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Factors such as insufficient heat dissipation and excessively high temperature can easily lead to demagnetization of the PMs in permanent-magnet (PM) motors. As a result, the magnetic field distribution of the motor will not be uniform, producing fault harmonics and lowering the operational performance of the motor. An essential stage in the diagnosis of faults and the monitoring of motor condition is the establishment of an accurate model of motors with demagnetization faults. In this paper, demagnetization faults are modeled by changing the Fourier coefficients in the Fourier expansion of the magnetization of PMs. This model can be used to determine the motor performance under various types of demagnetization, including radial air gap flux density, back electromotive force (EMF), and torque. On this basis, the corresponding relationship between the demagnetization degree and the fault signature is established, to provide a theoretical foundation for the subsequent demagnetization fault diagnosis. The finite element analysis (FEA) verifies the effectiveness and superiority of the proposed analytical model. The modeling method proposed in this paper can be applied to PM motors with PMs having different magnetization directions and shapes because it is based on the demagnetization region of PMs.

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Online Rotor Fault Diagnosis of Permanent Magnet Synchronous Motors Based on Stator Tooth Flux

Cited by 38 publications

References 25 publications

Disambiguation of Uniform Demagnetization Fault From Position Sensor Fault in FOC PMSM Applications

Disambiguation of Uniform Demagnetization Fault From Position Sensor Fault in FOC PMSM Applications

A Review of Modeling and Diagnostic Techniques for Eccentricity Fault in Electric Machines

Analytical Modeling and Analysis of Permanent-Magnet Motor with Demagnetization Fault

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