Neural network pressure identifier of a pumping unit with asynchronous electric drive of a centrifugal pump

The article considers the development of a pressure identifier for a pumping unit with an asynchronous electric drive. The widespread use of such installations determines the relevance of this subject. The purpose of the study is to develop a pressure identifier for a pumping unit as a part of an electrical complex based on neural networks. The current pressure value is calculated using the values of the stator current and voltage of the asynchronous electric motor. In the article under consideration, direct neural networks and nonlinear autoregressive networks with external input parameters are used to determine pressure, in contrast to existing methods for indirectly determining pressure.. Furthermore, to increase accuracy and reduce noise, the values of stator current modules of the electric motor and the value of the stator current voltage module are supplied to the network input. As a result, the author obtains structures of neural network pressure identifiers with asynchronous electric drives and also determines the sizes of the hidden layers using integral criteria. The article provides comparative pressure waveforms showing the operability of the neuroidentifier.