FIELD: electricity.
SUBSTANCE: invention relates to the field of diagnostics of electromechanical equipment technical condition that allows to diagnose and estimate the residual life of an asynchronous motor operating in various operating conditions by recording electrical and vibration parameters using vibration, current and voltage sensors and using an artificial neural network (ANN) for complex analysis of electrical, vibration and indirect parameters with further evaluation of technical condition and forecasting the probability of failure-free operation of the electric motor (EM). The method allows to diagnose and estimate the residual life of an electric drive based on an asynchronous motor operating in various operating conditions by recording electrical and vibration parameters, using vibration, current and voltage sensors and their complex analysis using an artificial neural network that allows for prediction and estimation of residual resource.
EFFECT: improved accuracy and quality of the electromechanical equipment condition and residual life estimation, taking into account the quality of the supply network and the operating conditions, based on the obtained values of the residual resource, taking into account the detected conditions based on the work of an artificial neural network, including analysis of electrical, vibrational and indirect parameters and detected defects.
5 dwg
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Authors
Dates
2017-07-24—Published
2016-11-10—Filed