Automatic Monitoring Method Of High Precision Drinking Water Quality Parameters And Application Research

With the rapid development of Chinese economy,environmental and safety issues have become increasingly prominent,especially water pollution problems.In recent years,problems in drinking water have often been reported in newspapers and have attracted the attention of the whole society.The water quality management method has gradually evolved from manual management to automatic management.Due to the wide range of drinking water quality and the large impact,it is of great practical significance to design a reasonable and feasible automatic detection algorithm for drinking water safety to reduce the error rate between automatic monitoring of abnormal forecast results and manual test results,Firstly,the paper analyzes the development history of water quality monitoring and the current development trend of drinking water quality monitoring methods.Aiming at the problem of high false alarm rate of water quality abnormal forecast due to the error of sensor data in automatic water quality monitoring,a self-learning drinking water safety detection algorithm based on sliding window is proposed.The algorithm combines sliding window with machine learning techniques,using the periodic characteristics of the sliding window to frame multiple water quality monitoring data,according to different water quality features to use the corresponding limited machine learning method to deal with the water quality data.By expanding the size of the window,it can reduce the false alanrm message.Secondly,starting from the current trend of combining traditional industry application systems with mobile devices,taking advantage of the convenience and versatility of the Android system,combing with the automation requirements of the water quality management of water plants,in this paper,a drinking water safety monitoring and forecasting system based on Android is designed and developed for waterworks manager.Through demand analysis,overall architecture design,database design for the system,it is determined that the SOLite,SQL Server and other technologies is used for data storage and combing the JSON data frame protocol format with asynchronous HTTP technology is used for data exchange as technical route between the client and the server to periodically obtain the sensor data collected by the server.Finally,the relative real-time of the water quality warning function in the system is realized.At the same time,the self-learning drinking water safety detection algorithm supported by the sliding window is added to the system,which improves the accuracy and practicability of the system.Finally,taking the data of Xi'an Leyouyuan Water Plant as an example,the system was tested.The results show that the error between the results of water quality safety detection algorithm and the abnormal situation of actual of water quality is less than equal to 3.4%.The system has a low false alarm rate and can be operated stably and conveniently.It meets the basic requirements of the water plant management personnel for the water quality safety monitoring software.