Research And Application On Intelligent Temperature Compensation Algorithm Of Dissolved Oxygen Sensor In Water Quality Monitoring

Water resources are the foundation of social and economic development and an important resource for human survival.At present,the frequent occurrence of water pollution and water quality disasters has formed a huge obstacle to the production of human society.At the same time,because of the high cost,high power consumption,low accuracy,and complicated operation,the water quality monitoring stations used in China are difficult to promote on a large scale.This paper designs and implements a water quality monitoring system based on LabVIEW and NB-IoT with the design requirements of low power consumption,low cost,high performance,and long distance for water quality monitoring.First,the thesis focuses on the problem that the dissolved oxygen sensor used in the monitoring system is susceptible to temperature and leads to large measurement errors.In this paper,the temperature compensation model of BP neural network is established,and the initial weights and thresholds of BP neural network are optimized by using artificial intelligence algorithm genetic algorithm(GA),simulated annealing algorithm(SA)and thinking evolution algorithm(MEA).On this basis,the paper improves the temperature drop formula,and uses different optimized BP neural networks to compensate the temperature of the dissolved oxygen sensor.The results show that temperature compensation model of the improved SA-BP neural network achieve a good temperature compensation effect,and the measure error of the dissolved oxygen sensor is less than 0.1 mg / L.Then,according to the functional requirements of the water quality monitoring system,the thesis completes the overall system plan and software and hardware design.The system hardware platform integrates PH,conductivity,redox,and dissolved oxygen sensors,uses the STM32L151 chip as the core of the microcontroller module,and transmits the collected data to the LabVIEW software platform by the wireless communication module with the BC26 chip.The LabVIEW software platform completes data processing,display,storage,and query,and establishes a weighted index evaluation model for water quality monitoring parameters.Finally,The results of system tset in the simulated test environment show that the water quality monitoring system designed in this paper can meet the task requirements.