Investigation of the Pump Unit Control System With the Neural Network Productivity Estimator

S. Burian, Mykola Pechinik, M. Pushkar, A. Tytarenko
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引用次数: 5

Abstract

This article deals with the novel approach to evaluate the technological coordinates of a pump unit. This method is is based on the use of the theory of neural networks. The expanded methodology of design a productivity estimator using signals of pump pressure and motor power consumption is developed. It is shown that for the development of the estimator, is required preliminary information on the behavior of the desired coordinate when the task signal and disturbing actions in the system vary. The research of developed estimator by a method of mathematical modeling of pressure stabilization system is carried out. A comparison of the results of the system performance with the estimator and the calculated productivity value and the recommendations for the possible application of the proposed methodology are presented.
基于神经网络生产率估计的泵机组控制系统研究
本文讨论了一种计算泵机组工艺坐标的新方法。这种方法是基于神经网络理论的应用。提出了利用泵压力和电机功耗信号设计生产率估计器的扩展方法。结果表明,对于估计器的开发,当系统中的任务信号和干扰动作发生变化时,需要关于期望坐标行为的初步信息。利用压力稳定系统的数学建模方法,对开发的估计器进行了研究。将系统性能的结果与估计器和计算出的生产率值进行比较,并对所提出方法的可能应用提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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