Monitoring the Gas Turbine Start-Up Phase on a Platform Using a Hierarchical Model Based on Multi-Layer Perceptron Networks

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2022-12-01 DOI:10.2478/pomr-2022-0050
Tacjana Niksa-Rynkiewicz, A. Witkowska, J. Głuch, M. Adamowicz
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引用次数: 2

Abstract

Abstract Very often, the operation of diagnostic systems is related to the evaluation of process functionality, where the diagnostics is carried out using reference models prepared on the basis of the process description in the nominal state. The main goal of the work is to develop a hierarchical gas turbine reference model for the estimation of start-up parameters based on multi-layer perceptron neural networks. A functional decomposition of the gas turbine start-up process was proposed, enabling a modular analysis of selected parameters of the process. Real data sets obtained from observations of the turbo-generator set located on a North Sea platform were used.
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基于多层感知器网络的分级模型在平台上监测燃气轮机启动阶段
摘要通常,诊断系统的操作与过程功能的评估有关,其中诊断是使用根据标称状态下的过程描述准备的参考模型进行的。该工作的主要目标是开发一个基于多层感知器神经网络的分级燃气轮机启动参数估计参考模型。提出了燃气轮机启动过程的功能分解,从而能够对该过程的选定参数进行模块化分析。使用了从北海平台上的涡轮发电机组的观测中获得的真实数据集。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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