基于神经网络的污水处理设备监测CPS设计

摘要

At present, most of the sewage treatment equipment is monitored by monitor with single sensors, so the fault recognition rate is low.In this paper , a set of new monitoring system for sewage treatment equipment is developed.The principle is that according to the comprehensive plan based on the requirements of cyber-physical system (CPS), BP neural network algorithm is used to process the data obtained from the sensor to monitor the different states of the equipment.For this system, Hardware chip of STM32, industrial Ethernet and serial communication, PC application software developed by C # language, and web remote monitoring system developed by HTML, JavaScript and C# language are used.Tests show that this system is running efficiently and the fault recognition rate is higher.%现阶段大部分污水处理设备使用单一传感器监测设备,故障识别率低.该文研发了一套新型污水处理设备监测系统,根据信息物理融合系统(CPS)的要求全面统筹,采用BP神经网络算法处理由传感器得到的数据,监测设备的不同状态.硬件芯片采用STM32,采用工业以太网和串口通信,采用C#语言开发上位机应用软件,采用HTML和JavaScript以及C#语言开发web远程监测系统.经测试,系统运行良好,故障识别率高.