Diagnosis And Analysis Of Fault Degree Of Heating Pipe Network Fault Based On Fuzzy Neural Network

With the rapid economic development,the scale of urbanization heating is increasing,followed by the occurrence of heating failures.With the continuous development of computer technology,in order to improve the economic and social benefits of heating systems,the use of intelligent means of centralized heating system for real-time monitoring and management is the trend of modern development.This paper attempts to use fuzzy neural network to diagnose the degree of damage to the heating pipe network,mainly to do the following aspects of research work:This paper summarizes the common intelligent methods of fault diagnosis of heating pipe network,summarizes the current situation of heating development both at home and abroad,the research status of heating accident,and the research and progress of heating pipe network fault diagnosis.The basic theoretical knowledge of BP neural network and fuzzy logic system is summaried.The situation of heating system of Handan City Thermal Power Company is analyzed,and the example of heating pipe network fault is proved to predict the importance of heating system failure,and make suggestions for heating pipe network operation.Analyze the causes of the failure of the heating pipe network and put forward the measures to deal with the failure.The BP neural network is used to diagnose the heating pipe network.The training and simulation of the model are realized by MATLAB software.The results show that BP neural network can be used for fault diagnosis,but it also finds that there are many disadvantages of BP neural network.In order to avoid the shortcomings of the model,this paper decides the BP neural network and the fuzzy logic system to be used together for the heat pipe network fault diagnosis analysis.The membership function is used to fuzzify the sample data,and the fuzzy neural network is constructed according to the fuzzy rules and the fuzzy reasoning combined with the BP neural network to diagnose the heating pipe network.Taking the damage degree of the thermal pipe network in Handan as an example,the input factors are the completion time,the commissioning time,the pipe diameter and the output factor as the fault damage degree.Using MATLAB procedures for training and simulation,The simulation results show that the fuzzy neural network is faster and more accurate than BP neural network,and the fuzzy neural network can be used in the fault diagnosis ofheating pipe network.