Eccentricity detection procedure in electric motors by force transducer and search coils in a novel experimental test bench

Galfarsoro, Unai; McCloskey, Alex; Hernandez, Xabier; Almandoz, Gaizka; Zarate, Sergio; Arrasate, Xabier

doi:10.1109/demped.2019.8864857

Cited by 6 publications

(2 citation statements)

References 14 publications

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“…[156]- [158], shims mounted in the bearing housing [145] or on the motor shaft [147], [148], by modelling misalignment [159], by moving the rotor relative to the stator [153], [154], [160] or by eccentric shaft housings [152]. The level of modelled eccentricity can be controlled by measuring the radial force induced by the unbalanced magnetic pull, which is constant in space for static eccentricity and rotates with the rotor for dynamic eccentricity [160].…”

Section: B Eccentricity Faultsmentioning

confidence: 99%

“…The basic diagnostic signals in eccentricity diagnosis are: stator current [135], [143]- [146], [150], [151], [156]- [159], [161], [162], mechanical vibrations [149], [155], [156], noise [155], an airgap search coil voltage [149], [152], [156], [160], stator voltage [159], speed [159], load torque [159], d-axis stator inductance Ld [147], [148], BEMF [160] and unbalanced magnetic pull [153], [154], [160].…”

Section: B Eccentricity Faultsmentioning

confidence: 99%

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Fault Diagnosis and Fault-Tolerant Control of PMSM Drives–State of the Art and Future Challenges

et al. 2022

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The issues of monitoring and fault diagnosis of drives with permanent magnet synchronous motors (PMSM) are currently very topical due to the increasing use of these drives in safety-critical devices. Every year, more and more articles on this subject are published. Therefore, the aim of this article is to update the overview of diagnostic methods and techniques for PMSM drives. Each of the main chapters of the article focuses on a specific element of the drive system (motor, power converter, measuring sensors), with particular emphasis on the components of the motor (stator windings, magnets, bearings, rotor). The main sections on PMSM fault diagnosis are divided according to the type of methods used to obtain the symptoms of the damage. In addition, a review of methods using the analysis of control structure signals for the diagnosis of damage to a vector-controlled motor is presented, as well as the latest achievements of researchers in the field of shallow and deep neural networks for the detection and classification of PMSM drives failures. Based on the presented literature analyses, some development trends and challenges related to the development of diagnostics and fault-tolerant control of PMSM drives are discussed in the conclusion part.

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