Research On Pulse Discharge Characteristics Of Plate Ozone Generator

Ozone is a chemical gas with extremely strong oxidizing and sterilizing properties.Due to its high efficiency and green characteristics,it is widely used in industrial wastewater treatment,tap water disinfection,food processing,medical and health fields.At present,the main method for preparing ozone with high concentration and high output in industry is the Dielectric Barrier Discharge(DBD)method.The DBD type ozone generator still has the problems of poor stability and high energy consumption,and the domestic Ozone generators generally use open-loop control,and the production efficiency of ozone is relatively low.With the increasing demand for ozone in environmental protection applications,in-depth study of the input and output relationship of ozone generation is the core content of improving ozone production efficiency and precise control of the system.This article takes the DBD plate ozone generator as the research object,and builds a 500g/h ozone generator experimental platform,covering five parts: power supply,plate ozone generator,oxygen source,cooling system and central control system.The system power supply has been further improved,and a higher frequency power supply has been designed with a frequency of 20 k Hz.Design the central control system to realize the control and data display of the platform,and propose a perfect data collection and management plan.The sensor data of the experimental platform is transmitted to the central control system via the 485 bus and the Modbus protocol,and then the data is transmitted to the cloud data center by means of 4G wireless transparent transmission to realize the remote interconnection and real-time monitoring of the experimental platform.Through a large amount of experimental data,the characteristics of pulse discharge were analyzed,and the influence of typical factors such as temperature,oxygen flow,pressure,power supply voltage and power supply pulse frequency on ozone concentration was studied.The experimental results show that when the temperature exceeds 33°C,the increase in temperature has a more obvious inhibitory effect on ozone generation.Increasing the flow rate within a certain range will help increase the ozone concentration,while too much flow will cause the ozone to be diluted and the concentration will decrease.The pressure change is also related to the oxygen flow rate,increasing pressure is accompanied by an increase in flow rate and a decrease in ozone concentration,but the output of ozone increases as the pressure increases.When the discharge degree of the discharge chamber reaches saturation,continuing to increase the power supply voltage will not cause the ozone concentration increases.When the power supply frequency is at the system resonance point,the higher the power supply pulse frequency can increase the discharge density of the discharge chamber and promote the generation of ozone.This article starts from the problem that the process of producing ozone by dielectric barrier discharge is complicated and easily affected by multiple factors.Using experimental data combined with artificial neural network methods to build a model of the ozone generation system,using typical impact factors as the input neurons of the model,and ozone concentration as the output neurons of the model.Using genetic algorithm(GA)to optimize the BP neural network(GA-BP)can quickly establish a more accurate system model,and propose an online model update plan based on the actual system operating characteristics to improve and optimize the offline model,effectively ensuring that the model can meet the actual system changes.The conditions of the experimental platform and the accurate prediction of the model provide the hardware foundation and theoretical basis for further research.