Combining response surface and particle swarm optimization for controlling smoke and dust concentration in factory buildings
To reduce the harm of high concentrations of smoke and dust generated during the operation of factory buildings to human health,we propose a response surface and particle swarm optimization method for factory smoke and dust concentration control.First,the single factor experiments are employed to determine environmental parameters and the specific range of temperature,relative humidity,wind speed,and air pressure,all of which exert significant impacts on smoke and dust concentration.Temperature,wind speed,relative humidity,and air pressure are selected as optimization parameters,with the concentration of factory smoke and dust as the optimization objective.Then,based on the response surface method,the regression equation between temperature,relative humidity,wind speed,and pressure and smoke concentration is obtained and variance analysis is performed.The regression equation is optimized using particle swarm optimization algorithm.Our results show when the temperature is 26℃,the air pressure is970.2 hPa,the relative humidity is70%,and the wind speed is1.25 m/s,the optimal solution for the objective optimization function of reducing smoke and dust concentration is 3.786 2 mg/m3.Compared with the traditional response surface method,the combination of particle swarm optimization algorithm is introduced to control the concentration of smoke and dust within the national standards and thus better protect the workers'health.
国家科技期刊平台
NSTL
万方数据
