【作者】 于泊蕖；

【导师】 尹连庆； 何凤鸣；

【作者基本信息】 华北电力大学 ， 环境工程， 2001， 硕士

【摘要】 本文旨在建立火电厂水力输灰管道结垢预测模型。首先，针对结垢速率影响因素问题展开研究，通过大量实验，找出主要影响因子并绘出影响规律曲线，对所得曲线进行回归分析，得到各单因素与结垢速率间的数学关系式。然而，灰管结垢趋势和结垢程度是众多因素综合作用的结果，单纯的数学方法是难以解决这一问题的，因此，在论文后一部分，引进计算机前沿科学—人工神经网络技术，直接从成垢的各种因素出发，利用网络的自学习和联想记忆能力，建立满足误差要求的灰水系统结垢预测模型。更多还原

【Abstract】 This paper aims at building up the scale prediction model in pipe of the hydraulic transport ash in coal-fired power plant.Firstly,the influencing factors of the scale rate are discussed and four primary factors and their effect laws by experiments are adduced.Next the graphs derived above are regressed and the relationship between the factors and the scale rate are given.but,the production of scale is a result of numerous factors,it hard to solve the problem by mere mathmatical methods,as a matter of fact, in the later part of the paper,Artificial Neural Networks is proposed,making use ofof its self-educated and the abilities of imagination and memory, a scale prediction model in the wet-ash trandportation system is build up at last.Yu Boqu( environmental Engineering)Directed by Prof. Yin LianqingAssociate Prof. He Fengming更多还原