利用递归神经网络监测蒸汽电厂蓄热式换热器

IF 3.3 3区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Journal of Artificial Intelligence and Soft Computing Research Pub Date : 2021-01-29 DOI:10.2478/jaiscr-2021-0009

Tacjana Niksa-Rynkiewicz, Natalia Szewczuk-Krypa, A. Witkowska, K. Cpałka, Marcin Zalasiński, A. Cader

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引用次数: 10

摘要

摘要人工智能算法在工业应用中的应用越来越多。它们的重要功能是支持诊断系统的运行。本文提出了一种基于递归神经网络（RNN）的新方法来监测蒸汽发电厂再生换热器。使用实际数据对所提出的方法进行了测试。这种方法可以很容易地适用于其他工业动态对象的类似监测应用。

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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Monitoring Regenerative Heat Exchanger in Steam Power Plant by Making Use of the Recurrent Neural Network

Abstract Artificial Intelligence algorithms are being increasingly used in industrial applications. Their important function is to support operation of diagnostic systems. This paper presents a new approach to the monitoring of a regenerative heat exchanger in a steam power plant, which is based on a specific use of the Recurrent Neural Network (RNN). The proposed approach was tested using real data. This approach can be easily adapted to similar monitoring applications of other industrial dynamic objects.

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来源期刊

Journal of Artificial Intelligence and Soft Computing Research COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-

CiteScore

7.00

自引率

25.00%

发文量

审稿时长

24 weeks

期刊介绍： Journal of Artificial Intelligence and Soft Computing Research (available also at Sciendo (De Gruyter)) is a dynamically developing international journal focused on the latest scientific results and methods constituting traditional artificial intelligence methods and soft computing techniques. Our goal is to bring together scientists representing both approaches and various research communities.