Research And Implementation Of Fault Diagnosis For Environmental Monitoring System Of Internet Of Things In Desert

Internet of things technology is regarded as the third wave of information revolution after computer and Internet technology.At present,Internet of things technology has been widely used in various fields,especially in the field of environmental monitoring.In the process of desert management,the intelligent monitoring of desert special environmental information is realized by setting up a special Internet of things system,which can provide data support for desert scientific ecological management.Because of the complexity and abominability of desert environment,the stability and reliability of the Internet of things system for desert special purpose is challenged.In the desert environment,the Internet of things system is often subject to the impact and damage of many kinds of harsh external environment,such as high temperature,low temperature and strong ultraviolet radiation,which is easy to cause system collapse,inaccurate data collection,unstable data transmission and other failures.In order to improve the stability and reliability of the Internet of things system in the desert area,as well as the timeliness and convenience of system maintenance,make full use of the fault diagnosis theory and technology,carry out the research on the fault diagnosis technology of the Internet of things system in the desert,and study the fault diagnosis method of the Internet of things in the desert,so as to lay a foundation for the intelligent diagnosis and remote or automatic fault processing of the Internet of things system.Specific research contents are as follows:(1)Based on the analysis of the faults in the desert Internet of things system,this study determines the common fault types and fault symptom information of the system,and studies and establishes the relationship between the fault types and fault symptom information of the system.The method of fault diagnosis is studied and the scheme of fault diagnosis based on BP neural network is proposed.(2)The fault diagnosis classification method is studied by using BP neural network.Fault diagnosis and classification are carried out with A Mu Gulong B,Yang Shuchai Deng,Gansu Gulang,Xinjiang South Xinjiang breeding base and Tibet Shannan fault diagnosis.The accuracy rate of fault diagnosis is 76.79%.In order to further improve the accuracy of fault classification,a quantum ant colony optimization algorithm is proposed.By introducing the quantum ant colony optimization algorithm to optimize the weight and threshold of BP neural network,the accuracy of the optimized model is achieved 90.94%.It greatly improves the accuracy of fault diagnosis.The introduction of the quantum ant colony optimization algorithm solves the problem that the BP neural network diagnosis model falls into the local optimum,which can well classify and predict the fault,and significantly improve the accuracy of fault diagnosis.(3)The fault diagnosis model is used to realize the automatic diagnosis of fault types.Combined with the actual needs of desert Internet of things system maintenance,the system is designed from the perception processing layer,network communication layer and application service layer respectively.The fault diagnosis system of desert Internet of things is researched and realized,and the automatic diagnosis and treatment of fault types of desert Internet of things system is realized.