Mohsen Zafarani

Discernment of Broken Magnet and Static Eccentricity Faults in Permanent Magnet Synchronous Motors

This paper deals with the discernment of broken magnet and static eccentricity faults in permanent magnet synchronous motors through the stator phase current. Broken magnet and static eccentricity faults exhibit very similar fault patterns in back-electromotive force (emf) and flux spectrums. Therefore, it is essential to separate these faults from each other for a true diagnosis. In this study, stator emf and phase current waveforms are analyzed in detail to identify the discerning components and characterize their dynamic behaviors. Two-dimensional time-stepping finite-element simulations and experimental results show that the fault classification process can be implemented by using fault-dependent in-phase current fault signatures.

A Comprehensive Magnet Defect Fault Analysis of Permanent-Magnet Synchronous Motors

In this paper, magnet defect faults and their corresponding reflections on permanent-magnet (PM) motor stator variables are investigated. An analytical approach based on a partitioned magnetic equivalent circuit is developed to determine the influence of magnet defect faults on PM motor variables. Due to the flexibility of the proposed method, the effect of each rotor magnets on each stator coil can be calculated to obtain the induced back electromotove force under faulty cases and observe the fault-related signatures in the frequency spectrum. The proposed tool significantly reduces the computational burden and provides sufficient accuracy, which significantly eases to simulate several magnet fault scenarios and examine detailed topology dependence relations in shorter time. Different cases, including various numbers and locations of defected magnets, winding configurations, and crack direction effects, are studied to understand the magnet defect influences comprehensively. The experiments and simulations are carried out at different speeds and load conditions to fully characterize the fault signatures. Comparative 2-D finite-element simulations and experimental results justify the theoretical magnet defect fault analysis and show the efficacy of the proposed approach.

Modeling and Dynamic Behavior Analysis of Magnet Defect Signatures in Permanent Magnet Synchronous Motors

In this paper, a motor specific fault severity assessment method is proposed to calculate the amplitude of magnet defect fault signatures in the stator current and back-electromotive force (EMF) through machine and controller parameters of permanent magnet synchronous motor (PMSM) drive. A detailed mathematical analysis is developed based on the linear model of PMSM to predict the behavior of fault signatures in motor variables at various operating points. In order to understand and decouple the effects of motor controllers and operating points, the derivations are further extended to clarify the effects of current loop gains. Under the light of findings, the fault severity impact on the current and back-EMF fault signatures is investigated exhaustively. For this purpose, the fault intensity imposed to a motor is increased in four steps by removing 25% of one magnet at each step. Throughout each fault level, the changes in the corresponding spectrums are analyzed, which provides an essential information to design accurate threshold to minimize false alarms. The theoretical derivations are validated through comparative finite element analysis (FEA) simulations and experiments.

Comprehensive Analysis of Magnet Defect Fault Monitoring Through Leakage Flux

This paper presents a detailed magnet defect fault detection analysis through fluxgate sensors by monitoring the leakage flux around permanent magnet synchronous motors. The flux spectra of electric machines contain direct and most critical information to monitor and characterize magnet defect faults and their progressions. In the mainstream diagnosis techniques based on phase current and back-EMF analysis, the fault corresponding signature characteristics may vary and cause misleading results depending on motor topology, winding configuration, number and location of defective magnets, and controller parameters. In this paper, it is shown that leakage flux analysis provides some superior results for magnet defect diagnosis. For this purpose, the fault patterns in the leakage flux spectrum are exhaustively analyzed at different torque/speed profiles. Simulation and experimental results show that the deployment of a direction sensitive fluxgate sensor in magnet defect fault detection yields very promising results both in time and frequency domain analyses.

Analysis and Detection of Inter-Turn Short-Circuit Fault Through Extended Self-Commissioning

This paper presents a comprehensive analysis of permanent magnet synchronous machine stator winding impedance variation in inter-turn short-circuit and eccentricity faults. The phase impedances are monitored through an extended self-commissioning procedure at the standstill mode before or after operation, and hence are agnostic to well-known issues caused by transients, load/speed level, or controller coefficient dependency. Moreover, the effect of stator iron core saturation on the electrical parameters is analyzed in depth. In order to distinguish the inter-turn shorts from the eccentricity fault which exhibits similar behaviors, a classification algorithm based on the saturation effect is introduced and analyzed on the machines with different pole–slot combinations. Both two-dimensional finite element analysis simulation and experimental test results are provided to show the efficacy of this analysis.

A simplified mathematical approach to model and analyze magnet defects fault signatures in permanent magnet synchronous motors

This paper deals with modeling and analysis of broken magnet fault signatures in permanent magnet surface mounted (PMSM) motor variables. A detailed mathematical analysis based on the linear model of PMSM motor is developed to predict the behavior of different fault signatures in stator current and back-emf for various motor operation points. In order to verify the results, a three phase, 8-pole PMSM motor is modeled using finite element analysis (FEA) and 7% of one magnet is cut using a fine cutter on the rotor to model the broken magnet fault. This paper also presents a comprehensive fault severity analysis and its impacts on the current and voltage fault signatures. For this purpose, the fault intensity imposed to the motor is increased in four steps by removing 25% of one magnet at each step. Throughout each fault level, the changes in the spectrum are analyzed which provides an essential information to design threshold fault detection.

Separation harmonics for detecting broken bar fault in case of load torque oscillation

This paper presents separation harmonics to discriminate rotor failure from low frequency load torque oscillations in three phase induction motors. The most common method for detecting broken rotor bar faults is to analyze the corresponding sidebands through motor current signature analysis (MCSA). If a motor is subjected to load fluctuation, then the oscillation related sidebands exhibit similar behaviors as well. Particularly, when the load fluctuation frequency is close or equal to that of broken bars, the stator current spectrum analysis can be misleading. In this study, torque and motor phase voltage waveforms are exhaustively analyzed to discriminate broken rotor bar fault from low frequency load torque oscillation in three phase induction motors. In order to extract and justify the separation patterns, 2-D Time Stepping Finite Element Method (TSFEM) is used. The simulation and experimental results show that the proposed approach can successfully be applied to fault separation process in star connected motors.

A simplified numerical approach to analyze magnet defects in permanent magnet synchronous motors

Condition monitoring of permanent magnet synchronous motors (PMSMs) is the process that identifies and averts impending faults and is of critical importance for reliability and robustness of overall system. In this study, magnet defect fault in PMSMs and the consequence effects of such failure on stator back-emf and current wave forms are investigated through modified magnetic equivalent circuit (MEC). The proposed analytical approach is used to investigate the effect of magnet faults on the stator back-emf which significantly reduces the computational burden and provides high enough accuracy while predicting the additional harmonics in motor variables. The 2-D Finite Element (FE) results support the potential use of the proposed method for fault signature analysis. Simulations are also carried out at different speed and load condition to expose the faulty signature. Comparative experimental results conducted at the same conditions to show the efficacy of the proposed method.

Separation of broken magnet and static eccentricity failures in PMSM

This paper deals with the separation of broken magnet failures from static eccentricity (SE) fault using phase current information in permanent magnet synchronous motors (PMSMs). Broken magnet and SE faults exhibit very similar fault patterns in back-emf and flux spectrums. Therefore, these two faults should be discerned from each other for accurate diagnosis. In this paper, phase current waveforms are exhaustively analyzed at different speed and torque profiles to discriminate broken magnet from SE in PMSMs. In order to specify the behavior of sideband harmonics, 2-D Time Stepping Finite Element Method (TSFEM) is used. Simulation and experimental results show that some distinctive harmonics such as 0.25th, 0.5th and 0.75th can define the fault type in PMSMs.

Automatic fault diagnosis in PMSM using adaptive filtering and wavelet transform

In this paper, a novel fault diagnosis technique is developed for permanent magnet synchronous motors (PMSM) using discrete wavelet transform and support vector machines based on stators current waveform. An adaptive filtering scheme is developed to remove the fundamental component of the current waveform in order to increase the accuracy of fault diagnosis. For this purpose, the instant rotational speed of motor is estimated without use of any external sensor. Our fault diagnosis method achieves accuracy of 97.67% and can be used to detect two types of faults in a PMSM, i.e. broken magnet and eccentric faults. In this method only one stator phase current out of three phases is used. It is shown that the residual waveform after removing the fundamental component by the proposed adaptive filter is a rich source of information for fault diagnosis. This filtering scheme can be generalized to other rotary machine applications in which the current signal can be measured for fault analysis.