Research Of The Embedded System For Online Monitoring Of Water Quality Based On CAN Bus

Water resources are one of the most important fundamental resources for human survival and the development of society. With the rapid development of society and economy, water resource protection and monitoring have received more and more attention in recent years. Online monitoring of water quality plays important role in water resource protection. In order to overcome the drawbacks of domestic water monitoring devices, such as low precision and the difficulty to online measurement of water environment, we develop an embedded online water quality monitoring system based on CAN bus.The main work of this dissertation is as follows:1. Design of embedded online water quality monitoring system based on CAN bus networkTo meet the demands of high reliability, extendibility, and easy maintainability, an embedded online water quality monitoring system is developed based on CAN bus network. The modularized structure is used in the design of monitoring system. This system is divided into mutual independence modules, which include sensor measurement module, data processing module, and execution device module. These modules have been designed and implemented.2. CAN bus based communication among the modules of these monitoring systemCAN bus is selected as communication mode among the modules so as to meet the requirements of instantaneity, stability, and reliability. This work focuses on communication method based on CANopen application layer protocol. Hardware platform of CAN bus and the corresponding application layer program have been developed as well.3. Dynamic calibration of Ion selectivity sensor driftTo achieve online measurement of ion selectivity sensor under complex field conditions, we further study the drift characteristics of ion selectivity sensor. Ammonium ion selectivity sensor is taken for instance, a method of ion selectivity sensor dynamic calibration is proposed according to the experimental data. Ammonium sensor drift is compensated dynamically based on the proposed model to improve its measurement precision. This research will offer effective means for online monitoring of water quality.