RESTful Industrial Robot Safety Test Management System

The "14th Five-Year Plan" and the 2035 long-term target recommendations point out that the Internet,big data,artificial intelligence and other industries should be promoted to deepen the integration of various industries,and to promote the development of advanced manufacturing clusters.China's manufacturing industry is in the stage of developing from digital manufacturing to intelligent manufacturing.And,the intelligent application of industrial robots is the core technology of manufacturing transformation and upgrading.At present,the research on the development and safety testing of industrial robots is still in its infancy.Therefore,it is necessary to conduct in-depth research on industrial robot systems to provide support for the production and application of largescale industrial robots.In this paper,the SCARA robot system is used as the carrier to research and design the industrial robot safety test management system.Based on the construction of RESTful services,the data mining methods and data visualization methods of industrial robot systems are further studied.Firstly,this paper designs a framework of the industrial robot safety test management system.RESTful style and related technologies are used to construct a service architecture suitable for industrial robot systems.Compared with the SOAP service architecture,the architecture of this paper is low in coupling,and each module in the system is clearly divided,which satisfies the system's management of multiple subordinate subsystems.demand.Secondly,RESTful services are designed and implemented according to system requirements.The service adopts a semi-structured JSON data format,and uses a unified model to achieve data persistence.Besides,this service unified the RDP and Socket services used by the subsystem,which is compatible with multiple protocols,and designed a load based on LVS and Nginx,which has strong concurrent processing capabilities;this service realizes authentication and authorization based on JWT,which greatly increases service security.Then,a time series data mining method based on the SARIMA model is studied for the industrial robot system data.The industrial robot information is constructed as a multidimensional time series,and the advantages and disadvantages of the ARIMA and SARIMA models are compared and analyzed.The fitting effect of the model was verified by drawing Q-Q diagram and calculating RMSE.By establishing a model of outliers for data cleaning,and proposing a polynomial interpolation algorithm for position trajectory data,it can perform kinematics numerical interpolation on three-dimensional trajectory data.Finally,using the acquired time series data and subsystem data,the visualization application is realized.This paper uses microservice technology to build a platform framework,and designs a visualization application that supports complex data using Vue3's efficient response principle.A variety of data exploration methods are designed,and users can obtain and analyze system data using chart screening and analysis and prediction methods.After testing,the system has a very low network delay when the network load is high.