Design And Implementation Of Predictive Maintenance Configuration System For Cloud Intelligence

With the continuous improvement of intelligent manufacturing technology,the requirements for reliability and maintenance management of key equipment are also gradually increasing.Predictive maintenance is of great significance to reduce the non-failure downtime of key equipment and ensure the reliable operation of key equipment.The traditional predictive maintenance system design has information islands and the degree of configuration is not high.Therefore,this thesis starts with low-code programming technology,takes the cloud intelligent service of key equipment as the application background,designs the technical framework of the predictive maintenance configuration system,and establishes a Based on the drag-and-drop low-code programming visualization method,a predictive maintenance function library based on data mining is realized,and a predictive maintenance configuration system for cloud intelligence is developed.The specific work includes:(1)The technical framework of predictive maintenance configuration system for cloud intelligence is designed.Aiming at the problems of information islands and low degree of configuration in the development process of traditional predictive maintenance systems,this thesis introduces low-code programming technology and systematically outlines the work that needs to be involved in the system development process,including edge-cloud collaboration technology,low-code programming technology As well as the design of predictive maintenance function library,etc.,a cloud-oriented intelligent predictive maintenance configuration system technical framework with flexible drag and drop,diversified functions,and configuration is designed.(2)A drag-and-drop-based low-code programming visualization method is established.Aiming at the problems of low scalability,poor flexibility,and strong dependence on professionals in traditional programming and development technologies,through low-code programming technology and using visual function node encapsulation technology,a drag-and-drop low-code programming visualization method is established to achieve It has functions such as node custom encapsulation,node data injection and output,node data analysis,and node deployment,so that non-professionals can quickly build application development programs in the form of drag and drop.(3)Implemented the predictive maintenance function library based on data mining.Aiming at the problems of non-standard predictive maintenance function design,difficult porting,and poor integration,the predictive maintenance function library architecture was designed,the function library design specification was sorted out,and the function library design process was formulated.By analyzing the functions and functions of predictive maintenance,a method of building a function library model based on data mining is proposed,and a predictive maintenance function library with standardized design,diversified functions and user interface is realized.(4)A predictive maintenance configuration system for cloud intelligence is developed.Aiming at a configurable intelligent analysis system,the overall system architecture with loosely coupled front and back ends is designed.Through the design mode of B/S architecture,Fast Api+Vue.js front and back end technologies are used,and a low-code editing system is built in the cloud.Following the modular development method,functional modules such as remote data transmission,data caching,function library integration,and visualization node encapsulation data display were developed,and the development of a cloud-oriented intelligent predictive maintenance configuration system was realized.