Study On Prediction Model Of PM2.5 Purification Time Of Air Purifier

In recent years,with the rapid development of China’s economy,the problem of air pollution has become more and more serious,and people have paid more and more attention to indoor air quality.About 80%of everyone’s life is spent indoors,and indoor air quality directly affects people’s health.To reduce indoor particulate pollution,the use of air purifiers is a convenient and effective method.Various air purification technologies can effectively solve indoor air pollution problems.Various air purifiers have emerged on the market to improve indoor Air quality creates a healthy and comfortable indoor environment.However,at present,the overall degree of intelligence of the air purifier is not high,and with the development of intelligence,higher requirements are placed on the air purifier.Nowadays,when people use air purifiers,most of them are based on personal habits.They cannot determine the best operation mode of air purifiers,nor are they sure about the best purification effect of air purifiers.Therefore,this topic will study the purification time of PM2.5 particulates in air purifiers through a combination of numerical simulation and statistical analysis.By comprehensively exploring the changes of PM2.5 purification time under different influencing factors,a prediction model of PM2.5 purification time is obtained,and then an intelligent control scheme for the best operation mode of the air purifier is proposed,mainly including the following contents and results:(1)Through theoretical analysis,on the basis of thorough research on the movement mechanism of particulate matter,the force analysis during the movement and the performance parameters of the purifier,the PM2.5 purification time is determined as the research object,the initial concentration of PM2.5,the air supply angle,the room The area,room aspect ratio,air supply speed,elevation angle,personnel angle and personnel distance are taken as the influencing factors,and the value range of each influencing factor is determined according to the research needs.(2)In the simulation study,a small air purifier room model of the same size as the experimental environment cabin was first established,the accuracy of the model was verified through experiments,and then a large air purifier room model of different sizes was established,which was purified by simulation calculation The effect of the air supply direction of the device on the PM2.5 concentration distribution at a height of 1.1m indoors.The air supply direction is different.The time for the PM2.5 concentration at each measuring point to drop to 15μg/m~3 is also different.When the air supply direction is different from the measuring point When the location is the same,the purification time is the fastest.(3)Simulate the change of PM2.5 concentration at different indoor positions when the initial concentration of PM2.5,the direction of air supply,the area of the room,and the aspect ratio of the room are simulated in nine operating modes with different air supply speeds and elevation angles In the situation,the simulation results were analyzed using Origin software to obtain the time when the PM2.5 concentration fell to 15μg/m3,and the results were compiled into statistical regression data,a total of 3,300 purification data were obtained from9 sets of regression data.(4)Establish PM2.5 purification time prediction model.By performing regression statistics on 9 sets of regression data,firstly,SPSS software was used to perform multiple linear regression analysis on the 9 sets of regression data.By checking the fitting degree of the model,the fitting degree of the tM4,tM5,tM6,tM7,tM8,and tM9 models was better Well,choose a linear model,and further test the significance of the regression coefficients to obtain a PM2.5 purification time prediction model.For the models of tM1,tM2,and tM3,the linearity of the model is not good enough,using Python software to establish a nonlinear regression model,and finally through the significance test of the regression equation to finally obtain the PM2.5 purification time prediction model.And verify each regression model.(5)In view of the limitations of the original automatic mode of the air purifier,an intelligent control scheme for the operating mode is proposed.On the basis of the PM2.5purification time prediction model,first track the position of the personnel to determine the direction of air supply,then select the best operating mode according to the changes of various influencing factors,and finally judge the booster of the air purifier according to the purification time at each personnel position Whether the fan needs to swing horizontally to achieve the purpose of minimum purification time at the personnel position.Comparing the purification time under the intelligent control scheme with the original purification mode of the air purifier,the purification time of the PM2.5 under the intelligent control scheme is reduced by an average of 15%to 30%.The method of combining numerical simulation and statistical analysis adopted in this subject has established a PM2.5 purification time prediction model,and proposed an intelligent control scheme,which has laid the foundation for further research on the intelligent control of air purifiers.