Induction Motor's Bearing Condition Motoring and Diagnosis Applying Cloud Services and Artificial Neural Networks

Dambrauskas, Karolis; Vanagas, Jonas; Zimnickas, Tomas; Kalvaitis, A.; Bizimavicius, Tomas

doi:10.1109/aieee48629.2019.8977096

Cited by 2 publications

(1 citation statement)

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“…The elimination of one of the most susceptible to damage elements of DC electric motors, i.e., the mechanical commutator and brushes, made it possible to use BLDC motors in applications requiring increased durability. The authors in [ 1 ] presented the percentage share of individual failures in induction motors, which shows that more than 40% of failures are caused by bearing failures, while 38% are problems with the machine stator. Therefore, it can be concluded that in DC brushless motors, damage to these elements will also have a significant impact on the reliability of the device.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning for Sensorless Temperature Estimation of a BLDC Motor

Czerwiński

Gęca

Kolano

2021

Sensors

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In this article, the authors propose two models for BLDC motor winding temperature estimation using machine learning methods. For the purposes of the research, measurements were made for over 160 h of motor operation, and then, they were preprocessed. The algorithms of linear regression, ElasticNet, stochastic gradient descent regressor, support vector machines, decision trees, and AdaBoost were used for predictive modeling. The ability of the models to generalize was achieved by hyperparameter tuning with the use of cross-validation. The conducted research led to promising results of the winding temperature estimation accuracy. In the case of sensorless temperature prediction (model 1), the mean absolute percentage error MAPE was below 4.5% and the coefficient of determination R2 was above 0.909. In addition, the extension of the model with the temperature measurement on the casing (model 2) allowed reducing the error value to about 1% and increasing R2 to 0.990. The results obtained for the first proposed model show that the overheating protection of the motor can be ensured without direct temperature measurement. In addition, the introduction of a simple casing temperature measurement system allows for an estimation with accuracy suitable for compensating the motor output torque changes related to temperature.

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Section: Introductionmentioning

confidence: 99%