Prediction of Acoustic Noise and Torque Pulsation in PM Synchronous Machines With Static Eccentricity and Partial Demagnetization Using Field Reconstruction Method

Torregrossa, Dimitri; Khoobroo, A.; Fahimi, Babak

doi:10.1109/tie.2011.2151810

Cited by 138 publications

(70 citation statements)

References 21 publications

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“…The study of the eccentricity in such machines is particularly interesting because it is one of the causes of acoustic noise and undesired vibrations [3]. The static eccentricity is one of the typical case study which are of interest when comes to investigate the rotor-dynamic of rotating components in electrical machines.…”

Section: Introductionmentioning

confidence: 99%

Radial force control of Multi-Sector Permanent Magnet machines considering radial rotor displacement

Valente

Papini

Formentini

et al. 2017

2017 IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD)

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Section: Introductionmentioning

confidence: 99%

Radial force control of Multi-Sector Permanent Magnet machines considering radial rotor displacement

Valente

Papini

Formentini

et al. 2017

2017 IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD)

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“…Many studies have detected the demagnetization of PMs in various ways, such as by monitoring the zero-sequence voltage [4], using the harmonic components of linkage flux [5], and using the changes in i d value [6].…”

Section: Introductionmentioning

confidence: 99%

Demagnetization Detection for IPM-type BLDCMs According to Irreversible Demagnetization Patterns and Pole-Slot Coefficients

Kang¹,

Kim²,

Park³

et al. 2016

Journal of Power Electronics

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This paper proposes a method for detecting irreversible demagnetization using the harmonic analysis of back electromotive force (BEMF) in interior permanent magnet-type brushless DC motors. First, demagnetization patterns, such as equality, inequality, and weighted demagnetizations, are defined and classified by considering the possibility of demagnetization resulting from motor operating characteristics. Second, an available diagnostic model for the harmonic analysis of BEMFs is defined according to pole-slot coefficients because the characteristics of BEMFs under demagnetization conditions are affected by the combination of poles and slots. Third, BEMFs and their harmonic components under normal and demagnetization conditions are analyzed through simulation and experiment to verify the proposed demagnetization detection technique.

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“…In their proposed method, the d-axis is excited whenever the motor is stopped using an ac-dc signal, and the variation in the inductance pattern due to demagnetization or eccentricity faults is used to detect these faults. Torregrosa et al [12] investigated the acoustic variations and torque oscillations caused by partial demagnetization and eccentricity faults occurring in the motor. Ebrahimi and Faiz [13] detected static and dynamic eccentricity faults by monitoring the magnetic field and vibration in a 2D and 3D-modeled PMSM.…”

Section: Introductionmentioning

confidence: 99%

Mechanical fault detection in permanent magnet synchronous motors using equal width discretization-based probability distribution and a neural network model

Akar¹,

Hekim²,

Orhan³

2015

Turk J Elec Eng & Comp Sci

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This paper focuses on detecting the static eccentricity and bearing faults of a permanent magnet synchronous motor (PMSM) using probability distributions based on equal width discretization (EWD) and a multilayer perceptron neural network (MLPNN) model. In order to achieve this, the PMSM stator current values were measured in the cases of healthy, static eccentricity, and bearing faults for the conditions of three speeds and five loads. The data was discretized into several ranges through the EWD method, the probability distributions were computed according to the number of current values belonging to each range, and these distributions were then used as inputs to the MLPNN model.We conducted eighteen experiments to evaluate the performance of the proposed model in the detection of faults.The proposed method was very successful in full load and high speed for some experiments. As a result, we showed that the proposed model resulted in a satisfactory classification of accuracy rates.

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Prediction of Acoustic Noise and Torque Pulsation in PM Synchronous Machines With Static Eccentricity and Partial Demagnetization Using Field Reconstruction Method

Cited by 138 publications

References 21 publications

Radial force control of Multi-Sector Permanent Magnet machines considering radial rotor displacement

Radial force control of Multi-Sector Permanent Magnet machines considering radial rotor displacement

Demagnetization Detection for IPM-type BLDCMs According to Irreversible Demagnetization Patterns and Pole-Slot Coefficients

Mechanical fault detection in permanent magnet synchronous motors using equal width discretization-based probability distribution and a neural network model

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