Design And Implementation Of Remote Test And Real-time Monitoring System For Medical PSA Oxygen Generation Equipment

With the advancement of the third revolution of the information technology industry,the Internet of Things(Io T)technology is becoming increasingly mature,making information transmission and control between people and things and between things possible.PSA(Pressure Swing Adsorption)oxygen generation equipment,as an important facility to maintain the life and clinical treatment of patients,is extensively used in all levels of hospitals and community health service institutions.However,some hospitals are faced with the problems such as long installation time,high frequency of use,insufficient oxygen content,and excessive content of harmful gas impurity,which have become the focuses of drug test department.The traditional test method of annual regular sampling has the limitations such as long testing process,low digital integration,and lack of targeting in blind sampling.To overcome the above problems,a remote test and real-time monitoring system for medical PSA oxygen generation equipment was designed and developed based on the monitoring data provided by the medical equipment test institute and the actual business needs.At the same time,the time series prediction algorithm was used to realize early warning,which improves the work efficiency of the inspectors.The main work is as follows:(1)Investigated the test process of PSA oxygen generation equipment by the medical equipment test institute,analyzed the interaction between on-site test terminal and the data analysis platform,and completed the design of system demands,Io T monitoring equipment scheme,database and function module.The main functions include: monitoring management of oxygen generation,alarm data management,data diagnosis and analysis,equipment test report,unit management,and system maintenance,etc.(2)Completed system development based onfront and back separation and development technology of Spring Boot and Vue.The system adopts the Io T technology to test and monitor the oxygen generation equipment at any time,intelligently analyze and evaluate the monitoring data,and form effective safety warning for the use of oxygen generation equipment,so as to inspect the enterprises with problems,improve the accuracy of supervision,meet the hospitals' needs of self-inspection and self-control,reduce the incidenceof adverse events of medical devices,and ensure the safety of medical treatment.(3)Proposed time series prediction algorithm based on ARIMA model(Autoregressive Integrated Moving Average model)for the prediction of oxygen concentration and carbon monoxide content.Based on ARIMA model,with the historical data uploaded by the terminal sensor to the server as the training sample,the future operating status of the oxygen generation equipment was predicted,and the prediction results were presented in the form of visual charts.At the same time,an early warning can be given to the prediction object that deviates from the normal value interval.