本文選題：供熱管網　切入點：故障診斷　出處：《河北工程大學》2017年碩士論文　論文類型：學位論文

【摘要】：隨著經濟的快速發(fā)展,城鎮(zhèn)化集中供熱規(guī)模不斷增加,隨之而來的是供熱故障的發(fā)生。伴隨計算機技術的不斷進步,為了提高供熱系統(tǒng)的經濟效益和社會效益,利用智能化手段對集中供熱系統(tǒng)進行實時監(jiān)控和管理是現(xiàn)代發(fā)展的趨勢。本文嘗試用模糊神經網絡診斷供熱管網故障損壞程度,主要做了以下幾方面的研究工作:本文總結供熱管網故障診斷常用的智能方法,以及供熱系統(tǒng)國內外發(fā)展現(xiàn)狀、供熱事故研究現(xiàn)狀、供熱管網故障診斷研究和進展。概述BP神經網絡和模糊邏輯系統(tǒng)的基本理論知識。對邯鄲市熱力公司供熱系統(tǒng)情況進行統(tǒng)計,通過舉例供熱管網故障案例證明預測供熱系統(tǒng)故障的重要性,為供熱管網運行提出建議。分析供熱管網故障原因并提出應對故障的措施。采用BP神經網絡為模型對供熱管網進行診斷,運用MATLAB軟件實現(xiàn)了模型的訓練和仿真,結果證明了BP神經網絡可以用于故障診斷,但是也發(fā)現(xiàn)了BP神經網路存在很多劣勢。為了避免模型的缺點,本文決定將BP神經網絡和模糊邏輯系統(tǒng)結合在一起用于供熱管網故障診斷分析。運用隸屬度函數(shù)將樣本數(shù)據模糊化,根據模糊規(guī)則和模糊推理結合BP神經網絡形成模糊神經網絡結構,從而對供熱管網進行診斷。以邯鄲市熱力管網故障損壞程度為例,輸入因素為竣工時間、投運時間、管道管徑,輸出因素為故障損壞程度。運用MATLAB程序進行訓練和仿真,仿真結果表明模糊神經網絡比BP神經網絡收斂速度快、準確率高,模糊神經網可以用在供熱管網的故障損壞程度診斷。
[Abstract]:With the rapid development of economy, the urbanization of central heating scale increasing, followed by heating failure. With the continuous development of computer technology, in order to improve the heating system of the economic and social benefits, the use of intelligent means of modern trends in the development of central heating system for real-time monitoring and management. This paper attempts to use the fuzzy neural network fault diagnosis for damage, mainly do the following research work: This paper summarizes the commonly used methods of intelligent heating pipe network fault diagnosis, and the heating system at home and abroad, the research status of heating accidents, heating pipe network fault diagnosis research and progress. An overview of BP neural network and fuzzy logic system of the basic theory of knowledge. The statistics of the Thermotics Inc of heating system in Handan City, through the example of heating pipe network fault prediction system for heat proof case Fault importance, put forward the proposal for the heating network operation. The causes of malfunction of heat pipe network and put forward corresponding measures of failure. By using BP neural network to diagnose the heating network model, using the MATLAB software to realize the training and simulation model, results show that BP neural network can be used for fault diagnosis, but also found the BP nerve the Internet has many disadvantages. In order to avoid the shortcomings of this model, the BP neural network and fuzzy logic system are combined for analysis of heating network fault diagnosis. Using the membership function of the fuzzy sample data, according to the fuzzy rules and fuzzy inference BP neural network combined with fuzzy neural network structure, thus the diagnosis of heating network. To the extent of the damage fault heat pipe network Handan city as an example, the input factors for the completion time, operation time, pipe diameter, output factors for fault. The MATLAB program is used for training and simulation. The simulation results show that the convergence speed of fuzzy neural network is faster than that of BP neural network, and the accuracy rate is high. Fuzzy neural network can be used to diagnose the degree of fault damage in heating network.

【學位授予單位】：河北工程大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TU995.3

【參考文獻】

相關期刊論文 前10條

1 陳知富;;中小城市集中供熱的現(xiàn)狀問題及規(guī)劃發(fā)展探討[J];區(qū)域供熱;2016年02期

2 林俐;湯亞芳;張尚然;;基于改進BP算法的短期電力系統(tǒng)負荷預測[J];中小企業(yè)管理與科技(上旬刊);2015年07期

3 楊俊鋒;;模糊神經網絡在智能交通系統(tǒng)中的應用[J];黑龍江科技信息;2014年32期

4 張俊發(fā);喬晨曄;王魁吉;;供熱系統(tǒng)的安全運行與事故預防[J];區(qū)域供熱;2014年04期

5 段蘭蘭;田琦;段鵬飛;李哲;;基于遺傳優(yōu)化BP神經網絡的供熱管網故障診斷模型[J];中北大學學報(自然科學版);2014年03期

6 吉忠平;;大型供熱管網安全問題的分析與思考[J];同煤科技;2011年01期

7 牛培峰;張密哲;陳貴林;王懷寶;張君;竇春霞;;自適應模糊神經網絡控制在鍋爐過熱汽溫控制中的應用[J];動力工程學報;2011年02期

8 臧大進;曹云峰;;故障診斷技術的研究現(xiàn)狀及展望[J];西安文理學院學報(自然科學版);2011年01期

9 徐中堂;;六十年發(fā)展中的城市集中供熱[J];區(qū)域供熱;2010年02期

10 李培強;劉志勇;李欣然;汪l，

本文編號：1624400