基于多层神经网络的天然气抽气压缩机特性逼近

2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus) Pub Date : 2021-01-26 DOI:10.1109/ElConRus51938.2021.9396438

M. Shestopalov, R. I. Smirnov, D. Imaev

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引用次数: 3

摘要

比较了多层神经网络和非线性回归模型对天然气离心式压缩机特性的逼近结果。结果表明，压缩机特性的解析描述可以提高压缩机模型在工作点线性化系数的计算精度。

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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Approximation of the Natural Gas Pumping Compressor Characteristics using a Multi-layer Neural Network

Results of approximation of characteristics of a natural gas centrifugal compressor by a multi-layer neural network and a nonlinear regression model are compared. It is shown that the analytical description of the compressor characteristics makes it possible to increase the accuracy of calculating the coefficients of the compressor model linearized at the operating point.

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2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)

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