利用人工神经网络对电厂发电机可用性进行估计与分析

A. Awad, A. A. Ahmed, Osamah Abdulateef
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引用次数: 0

摘要

电厂大量的故障导致了工作的突然停止。在某些情况下,没有必要的备用材料进行维修,导致发电厂机组发电中断。本文研究了Al-Dourra电厂5号机组发电机可用性的确定问题。为了评估该发电机的可用性性能,已经进行了广泛的研究,以收集合适的细节级别的准确信息,以实现可用性分析的目标。采用威布尔分布,通过Minitab 17和人工神经网络(ann)进行可靠性分析,采用前馈、反向传播方法。使用2015-2017年运营数据,通过传统方法(威布尔分布)计算可用性并训练人工神经网络,使用2018年运营数据对模型进行验证。研究表明,人工神经网络可以预测发电机的可用性,人工神经网络预测的可用性与威布尔分布输出的相关系数(R)为0.99874,均方误差(MSE)为5.6937E-06。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimate and Analysis the Availability of Generator in Electric Power Plant Using ANN
The large number of failure in electrical power plant leads to the sudden stopping of work. In some cases, the necessary reserve materials are not available for maintenance which leads to interrupt of power generation in the electrical power plant unit. The present study, deals with the determination of availability aspects of generator in unit 5 of Al-Dourra electric power plant. In order to evaluate this generator's availability performance, a wide range of studies have been conducted to gather accurate information at the level of detail considered suitable to achieve the availability analysis aim. The Weibull Distribution is used to perform the reliability analysis via Minitab 17, and Artificial Neural Networks (ANNs) by approaching of Feed-Forward, Back-Propagation. Operating data from the years 2015–2017 were used to calculate the availability by traditional method (Weibull distribution) and train the ANNs, while data from the year 2018 of operation were used to verify the model. The study implies that the ANN may be able to forecast the availability of the generator with a correlation coefficient (R) 0.99874 and a Mean Square Error (MSE) 5.6937E-06 between the availability predicted by ANN and Weibull distribution output.  
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