离心压缩机的数学建模

V. Harasymiv, T. Harasymiv, O. Moyseenko
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引用次数: 0

摘要

本文旨在基于数据处理型神经网络的成组方法建立离心式压缩机的数学模型,以确定离心式压缩机的容积流量作为离心式压缩机工艺参数(转子角速度、压缩机进出口温度、压缩机进出口压力、大气压力)的依赖关系。这是一项重要的科学任务,因为大多数过程工业中使用的离心式压缩机都没有测量容积流量所需的设备。它不允许估计压缩机在运行过程中的技术状态。基于336个数据点(从现场测量中收集)并使用Dolyna天然气管道线性生产管理的天然气离心式压缩机(16ГЦ2-395/53-76C),对所开发的模型进行了验证。试验结果表明,该数学模型具有良好的有效性。关键词:容积流量,离心式增压器,数学模型,参数群考虑法,神经网络,工艺参数,相关系数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MATHEMATICAL MODELLING OF THE CENTRIFUGAL COMPRESSOR
The paper is aimed to create the mathematical model of the centrifugal compressor based on the group method of data handling-type neural networks to determine the compressor volumetric flow rate as the dependence on the centrifugal compressor’s technological parameters (the rotor’s angular velocity, the compressor’s inlet and outlet temperatures, the compressor’s inlet and outlet pressures, the atmospheric pressure). It is the important scientific task, because most centrifugal compressors used in the process industry don’t have equipment needed to measure the volumetric flow rate. It does not allow to estimate the compressor’s technical state during its operation. Verification of the developed model has been performed, based on the 336 data points (collected from the field measurements) and with using the centrifugal compressor of natural gas (16ГЦ2-395/53-76C) of Dolyna linear production administration of gas transmittal pipelines. The test results have been showed the adequate efficiency of the mathematical model. Keywords: volume flow, centrifugal supercharger, mathematical model, method of group consideration of arguments, neural networks, technological parameters, correlation coefficient.
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