Data Mining Based Ozone Generator System Barrier Detection And Power Control

With the development of artificial intelligence technology and the improvement of hardware computing capabilities,the industrial automation scheme based on data modeling is more and more feasible.It has become a trend to solve the industrial problem by using data mining technology.At present,the domestic ozone preparation technology is relatively backward compared with foreign countries.The ozone generator has low working stability and high energy consumption.Most large-scale generator systems adopt open-loop control and have low efficiency.If data mining technology can be used to refine the potential connections implied in a large amount of process data,and to obtain the mutual law between key data and use it as feedback from the system,not only can the stability and safety of the ozone generator be significantly improved,but also Can greatly improve production efficiency.In this paper,the ozone generator system is taken as the research object.In order to realize the closed-loop control scheme based on data mining technology,a remote monitoring system capable of intelligently detecting the fault of ozone generator is designed.Based on the original ozone generator system,this paper designs a resonant frequency detection module based on acoustic spectrum analysis for the resonant frequency measurement module,and collects the natural resonant frequency data and other key data obtained by the method.The cloud server is used to build a data management platform.After the ozone generator uploads many key data to the platform through the 4G module,the data is automatically stored and backed up,and the system status can be displayed in real time.By using the data management platform The stored historical data carries out a large amount of data mining work,and uses different data models to detect the two types of system faults.Finally,based on the test results,a closed-loop control scheme of system output power is developed.The ozone generator remote monitoring system designed in this paper effectively monitors the system status and faults,and uses the real-time fault information as feedback to control the system in closed loop.The frequency tracking method based on the fault information is automatically adjusted and the given frequency is fixed.The conventional method is compared.The results show that the frequency tracking method has higher output power,and the ozone generator closed-loop control system based on data mining technology has better performance.