| 基于人工神经网络的电站锅炉积灰实时监测系统 |
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| 引用本文： | 杨祥良,安连锁,孙鑫强,孙保民,沈国清.基于人工神经网络的电站锅炉积灰实时监测系统[J].动力工程,2010,30(3). |
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| 作者姓名： | 杨祥良 安连锁 孙鑫强 孙保民 沈国清 |
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| 作者单位： | 华北电力大学,电站设备状态监测与控制教育部重点实验室,北京,102206 |
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| 摘 要： | 针对燃煤电站锅炉对流受热面积灰,提出了一种基于人工神经网络的积灰实时监测方法:利用受热面清洁吸热量和实际吸热量定义灰污特征参数;通过电厂现有的DAS系统得到的温度、压力和流量等参数可获得大量样本点;建立神经网络模型并进行训练.在燃用神华煤的某300 MW锅炉上进行了试验.结果表明:实测吸热量与预测吸热量的最大误差不超过10%,平均误差为3%左右.该方法可准确预测锅炉对流受热面的积灰情况.
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| 关 键 词： | 燃煤锅炉 积灰 吹灰 人工神经网络 在线监测 |
Real-time Monitoring System for Ash Deposit in Utility Boiler Based on Artificial Neural Network |
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| YANG Xiang-liang
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AN Lian-suo
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SUN Xin-qiang
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SUN Bao-min
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SHEN Guo-qing.Real-time Monitoring System for Ash Deposit in Utility Boiler Based on Artificial Neural Network[J].Power Engineering,2010,30(3). |
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| Authors: | YANG Xiang-liang AN Lian-suo SUN Xin-qiang SUN Bao-min SHEN Guo-qing |
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| Affiliation: | MOE's Key Lab of Condition Monitoring and Control for Power Plant Equipment;North China Electric Power University;Beijing 102206;China |
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| Abstract: | Aiming at ash deposit on convective heating surface in coal-fired utility boiler,a real-time monitoring method for ash deposit based on artificial neural network was proposed.First,the fouling characteristic parameter was defined by use of the heat absorption of the clean heating surface and the actual heat absorption.Then a lot of samples of temperature,pressure and flow rate were obtained from the existing DAS system in the power plant.Finally,the artificial neural network model was established and traine... |
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| Keywords: | coal-fired boiler ash deposit sootblowing artificial neural network online monitoring |
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