FIELD: electricity.
SUBSTANCE: invention is related to the area of technical condition diagnostics for electrical wires, for example, for electric drives of rolling mills in metallurgical production on the basis of parameters analysis of current, voltage, speed and control setting with use of recurrent artificial neuron network. The concept of the invention is as follows: parameters of current, voltage, speed and control setting are measured with a certain time interval, and then parameters are converted to digital form and transferred to PC for processing. Before operation of the drive the software-based recurrent artificial neuron network trained for the specific electric drive reproduces dynamics of the drive parameters, thereupon results of the network model dynamics are compared with real dynamics of the electric drive. In faulty electric drive dynamics of its parameters deviate from the model dynamics and discrepancy function is calculated. By nature of discrepancy function evaluation of technical condition and forecast of the drive resource is made.
EFFECT: improved accuracy and reliability for diagnosing of emergency conditions of the electric drive at operating equipment at early stage and non-observed stage thus preventing sudden emergency shutdown of the electric drive and reducing repair costs.
2 dwg
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Authors
Dates
2015-04-10—Published
2013-10-16—Filed