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Application And Optimization Of Intelligent Early Warning Technology For Medium And Low Pressure Gas Regulator

Posted on:2021-01-04Degree:MasterType:Thesis
Country:ChinaCandidate:Q LiFull Text:PDF
GTID:2392330620466617Subject:Architecture and civil engineering
Abstract/Summary:PDF Full Text Request
Natural gas,as an indispensable clean energy under the acceleration of urban modernization,will continue to develop in the next few decades;in recent years,the gas industry has developed rapidly,and the new technologies and new regulations that have emerged will also gradually in the gas industry application.How to ensure the stability and safety of the gas transmission and distribution process has always been the focus of research in the field of gas.Gas pressure regulator is an important node to ensure the normal delivery of gas to all levels of pressure,from high-pressure gas source to sub-high pressure pipe network,sub-high pressure pipe network to medium-pressure pipe network,medium-pressure pipe network to low-pressure supply,the middle layer is decreasing,Are all using different pressure regulation gas pressure regulators for gradual transmission,so the study of gas pressure regulators will provide a reference in gas safety technology and guarantee the efficient and stable use of gas.Firstly,according to the working principle and typical fault characteristics of the gas pressure regulator,the fault diagnosis process of the pressure regulator is deeply researched,and the method in fault diagnosis is optimized.Discuss the different voltage regulators in the internal structure,analyze the process of voltage regulation and the principle of automatic control.Investigate its internal faults through phenomena and find solutions and common maintenance methods.Secondly,firstly analyze the obvious abnormalities of the gas regulator during operation,that is,the fault performance characteristics of the outlet pressure of the gas regulator,use the empirical mode decomposition method to extract the effective pressure information,and apply the energy value method and spectrum The feature method divides the thresholds of the decomposed IMF components in order to more accurately and effectively distinguish the signal of the outlet pressure in different states.Then,for the problem that the internal components cannot be investigated when the regulator fails,a fault diagnosis method of gas regulator based on Bayesian network is proposed.By analyzing several typical faults and performance characteristics of the voltage regulator,combined with expert experience to carry out probability statistics on the prior information;a Bayesian fault diagnosis network was established;in order to count the posterior information of the gas regulator,that is,calculate the regulator the probability of a specific failure.For example,the film is damaged,the main valve body seal leakage,etc.,further study of internal faults can optimize the manual disassembly and maintenance process,which has high economic and practical value.Finally,the fault diagnosis method of gas pressure regulator based on information fusion method,that is,the empirical mode decomposition method combined with Bayesian network(EMD-BEYES)gas fault diagnosis method is summarized.The empirical mode decomposition method is used to distinguish the fault characteristics of the voltage regulator,and then the probability of occurrence of each component is calculated by the method of Bayesian network.When the gas pressure regulator is faulty and needs to be repaired,the fault characteristic corresponding to the abnormality of the pressure regulator is prioritized to check the fault node with the highest probability.This method is superior to the previous fault diagnosis schemes.It can improve the accuracy of fault identification in the application process,and optimize the process in the disassembly and repair steps after diagnosis.Under the in-depth study of accumulating expert experience and historical faults,the pressure regulation make further engineering application and promotion in the intelligent process of device fault diagnosis.
Keywords/Search Tags:Gas pressure regulator, Fault diagnosis, Empirical Mode Decomposition, Bayesian network, Information fusion
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