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Heating Pipe Network Security Architecture Model Based on BP Artificial Neural Network

Author: GuoJia
Tutor: HaoXueJun
School: Beijing Construction Engineering College
Course: Heating,Gas Supply, Ventilation and Air Conditioning Engineering
Keywords: the security of heating accident factors response measures BP neuralnetwork security model
CLC: TU995
Type: Master's thesis
Year: 2012
Downloads: 53
Quote: 1
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Abstract


On the context of the rapid economic development and continuous improvementof living standards, China’s urbanization level is constantly moving forward. It isfollowed by the rapid development of the central heating business. However, with theheating industry continue moving forward and expansion, more and more heatingnetwork failures, accidents are also plagued the people. These problems haveseriously affected to the heating network of economic, security, reliability, and itssocial impact not be ignored.From heating development status, study and progress of the heating accident,emergency mechanism, fault diagnosis overview of the research status of the heatingsystem. There is an overview of the heating system in Beijing, an instruction about theimportance of the heating system safety, and a summary about the main securityproblem of heating system. This passage Collected accident cases of heating systemin Beijing; researched the root causes of security incidents, the detailed process of theaccident, the harm consequences and secondary disasters; and proposed incidentresponse measures of heating system.Based on the investigation of the law on the occurrence and development, wesummed up all the details of the security issues in the heating system and establishedthe security structure model of the heating system. In this paper, establish the structureof10-13-5of the BP neural network model. The input factors are corrosion, fatiguecracking, external damage, natural disasters and secondary disasters, improperoperation, carbonization of the insulation layer, diameter, fault time, the age ofpipeline. The output is the level of accident. By the MATLAB neural network toolbox,we programmed heating pipe network security evaluation model. By the test sampleto be tested to prove the accuracy of the model is acceptable.

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CLC: > Industrial Technology > Building Science > Municipal Engineering > Urban central heating
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