A review of Permanent Magnet Synchronous Motor fault diagnosis

ZhifuWang,; Yang, Jingzhe; Ye, Huiping; Zhou, Wei

doi:10.1109/itec-ap.2014.6940870

Cited by 19 publications

(5 citation statements)

References 25 publications

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“…This can be noticed as an error in the accuracy of level, temperature, or flow measurements. Also, it could be represented by uncalibrated or defective actuators such as motors and valves [3], [4].…”

Section: Introductionmentioning

confidence: 99%

Three Tank System Sensors and Actuators Faults Detection Employing Unscented Kalman Filter

Sayed

Aboelhassan

Hebala

et al. 2021

2021 IEEE 19th International Power Electronics and Motion Control Conference (PEMC)

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Fault detection is critical for industrial applications to maintain a stable operation and to reduce maintenance costs. Many fault detection techniques have been introduced recently to cope with the increasing demand for more safe operations. One of the most promising fault detection algorithms is the Unscented Kalman Filter (UKF). UKF is a model-based algorithm that could be used to detect different fault types for a given system. On the other hand, the three-tank system is a well-known benchmark that simulates many industrial applications. The fault detection of the three-tank system is quite challenging as it is a Multi-Input Multi-Output (MIMO) nonlinear system. Therefore, UKF will be employed as a fault detection strategy for this system to detect sensor and actuator faults. The performance of the UKF will be investigated under different operating and fault conditions to show its merits for the given case study.

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Section: Introductionmentioning

confidence: 99%

Three Tank System Sensors and Actuators Faults Detection Employing Unscented Kalman Filter

Sayed

Aboelhassan

Hebala

et al. 2021

2021 IEEE 19th International Power Electronics and Motion Control Conference (PEMC)

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“…Permanent Magnet Synchronous Motors (PMSMs) have been widely utilized in many crucial and critical applications such as propulsion for the railway, electrical trains, electrical vehicles, and recently electrical aircraft [1]- [4] as well as other safety critical application in chemical or petrochemical industries [5]. PMSMs have the privilege of being one of the highest efficiency motors, and currently have a very wide selection of speed-torque profiles as well as competing with very high torque and power density designs [6]- [9].…”

Section: Introductionmentioning

confidence: 99%

“…The PMSM may be exposed to fault's existence during the operation, these faults could be mechanical, electrical, or magnetic [9], [10]. In this context, an extensive range of studies was conducted for fault diagnosis of PMSM, especially for the safety critical applications.…”

Section: Introductionmentioning

confidence: 99%

Fault Tolerant Control Strategy Based on Model Predictive Control and Unscented Kalman Filter for Permanent Magnet Synchronous Motor

Aboelhassan

Sayed

Hebala

et al. 2021

2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA)

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Permanent Magnet Synchronous Motors (PMSMs) are now extensively used in many critical applications. There is an increasing need for the motor and control system to have fault tolerant capabilities. This paper presents a fault tolerant control strategy to operate the PMSM during inter-turn fault conditions. The proposed technique combines the Model Predictive Control (MPC) for the speed and current control loops, and an almost error-free Unscented Kalman Filter (UKF) to estimate the PMSM inter-turn fault ratio. The PMSM statespace model for healthy and faulty conditions will be presented. Also, the equations and the remedial action of the MPC and UKF are provided in detail. The proposed algorithm is applied to PMSM model as a case study with a range of simulation analysis and discussion of results.

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“…Researchers conducted many studies on the inter‐turn fault and proposed numerous diagnosis methods. Motor current signal analysis is a popular method because it is fast and efficient [9]. The commonly used signal processing methods are fast Fourier transform [10, 11], short‐time Fourier transform [12], and wavelet transform [13–15].…”

Section: Introductionmentioning

confidence: 99%

Inter‐turn fault diagnosis of permanent magnet synchronous machine based on tooth magnetic flux analysis

Zhang

Huang

Yang

et al. 2018

IET Electric Power Applications

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This study proposes a novel inter-turn fault diagnosis method for a permanent magnet synchronous machine. Search coils are set on every stator tooth to measure the tooth fluxes. The high-order harmonics produced by the inverter are adopted to diagnose the inter-turn fault existence and locate the fault tooth. The fault severity coefficient is proposed on the basis of theoretical analysis and can identify the fault severity. A comparative analysis of a traditional method based on co-simulation shows that the proposed method is sensitive and that the fault severity coefficient is accurate, intuitive and independent of the operating condition of the motor. An experimental platform is set up, and it validates the effectiveness of the proposed method.

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A review of Permanent Magnet Synchronous Motor fault diagnosis

Cited by 19 publications

References 25 publications

Three Tank System Sensors and Actuators Faults Detection Employing Unscented Kalman Filter

Three Tank System Sensors and Actuators Faults Detection Employing Unscented Kalman Filter

Fault Tolerant Control Strategy Based on Model Predictive Control and Unscented Kalman Filter for Permanent Magnet Synchronous Motor

Inter‐turn fault diagnosis of permanent magnet synchronous machine based on tooth magnetic flux analysis

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