Design And Development Of Gear Box Remote Diagnosis System Based On Edge-cloud Collaborative

Gear box is an important mechanical equipment in oil field and plays an important role in actual production.Traditional gearbox equipment monitoring and fault diagnosis methods have been able to diagnose equipment remotely.However,with the increase of enterprise demand and production scale,more and more devices are connected to cloud from production site,and the amount of data produced is exponentially increasing,which not only increases the resource storage cost but also the data transmission cost of enterprise cloud server.In this thesis,a remote gearbox fault diagnosis system based on edge cloud cooperation is designed and developed with the aim of effectively monitoring the gearbox operation state and accurately and quickly identifying the gearbox fault.The main elements are as follows:(1)Design of gearbox remote fault diagnosis system based on edge calculation.In view of the large traffic cost of traditional cloud remote fault diagnosis system in uploading field data,the advantages and necessity of edge computing in remote diagnosis are analyzed,a gearbox remote fault diagnosis system with edge computing function is designed,the data is pretreated and analyzed at edge layer,and the necessary data is transmitted to cloud for analysis.The analysis of data acquisition in the field shows that the design of this system can effectively reduce the data transmission by35%,reduce the traffic cost,avoid the risk of data leakage caused by repeated data transmission,and improve data security.(2)Frontier cloud-based collaborative fault diagnosis method.It usually takes a certain amount of time to upload the data and run the model for the use of traditional cloud fault diagnosis model.A gearbox fault diagnosis method based on edge cloud coordination is proposed.By using fuzzy proximity algorithm,the fault data collected are pre-diagnosed and the severity of fault is preliminarily judged.Cloud based on uploaded fault data and VMD-BP neural network gearbox diagnostics model for further fault identification and analysis to provide a basis for further maintenance.This method makes up for the fact that the traditional cloud fault diagnosis system is slow to respond to the field fault in the context of big data,so that the equipment fault diagnosis works more closely to the field.(3)Design and development of gearbox remote fault diagnosis system.The gearbox fault diagnosis system based on edge calculation is developed by ASP.NET,C#,My SQL and Ali Cloud,and the gearbox remote fault diagnosis system is combined with edge cloud collaborative fault diagnosis method.The equipment condition monitoring and fault preanalysis can be carried out by using the fault preanalysis system which can be accessed by Ethernet in the field.Remote monitoring,data analysis and fault diagnosis of gearbox can be realized by browsers.