Analysis Of Low Temperature Drying Characteristics Of Sludge And Heat Pump Drying System

The efficient treatment and recycling of sludge is not only a necessary requirement for ecological environment protection,but also a necessary requirement for improving the quality of life of urban and rural people.Sludge drying is an important method for sludge reduction.The use of heat pumps for low-temperature sludge drying is a clean and energy-saving drying method,which is conducive to the efficient utilization of resources and energy.It has also been widely recognized,but there is little research on the characteristics of heat pump drying under low-temperature conditions.Combining the experimental research and theoretical analysis,this thesis conducts experimental research on the low-temperature drying characteristics of sludge.Based on experimental data,a prediction model for the low-temperature drying process of sludge is analyzed to achieve accurate prediction of the sludge drying process,thereby improving drying efficiency and energy conservation.Finally,a heat pump drying system model is established by using the TRNSYS simulation software.Firstly,experiments of sludge in different thickness on low-temperature sludge drying were conducted under different air temperatures and relative humidity.And the characteristics of low-temperature sludge drying were analyzed.The research results showed that under the conditions of a thickness of 2mm to 6mm,a temperature of 40 ℃-60 ℃,and a relative humidity of 30%-60%,the drying time to reduce the relative humidity from 60% to 30% can reduce by about half;Every 10 ℃ increase in air temperature can reduce the drying time by15%-25%;Reducing the thickness of the sludge layer from 6mm to 2mm can reduce the drying time by about 2/3.Secondly,by using traditional drying models to fit the experimental data,it was found that the Midilli model had the best fit and was most suitable for describing the low-temperature sludge drying experiment in this thesis.Due to the inability to accurately find the mathematical relationship between the coefficients k and n of the Midilli model and the thickness of the sludge layer,air temperature,and relative humidity,in order to better express the drying characteristics of sludge,a mathematical formula was established for factors such as water ratio and the thickness of the thin layer,air temperature,and relative humidity.The effective diffusion coefficient was used to establish a relationship with them,and then the effective diffusion coefficient was used as a model parameter to establish a sludge drying prediction model,The accuracy of the model is similar to that of the Logarithmic model.The BP neural network is used to build the sludge drying prediction model.Among them,the Bayesian regularization training(Trainbr)algorithm is better than the Levenberg Marquardt training(Trainlm)algorithm in predicting sludge drying.In this study,the optimal number of hidden neurons is 30.The optimized BP neural network model has a good prediction accuracy,and the relative error with the experimental data is within 5%.Finally,the method and process for establishing a simulation model of a heat pump drying system on the TRNSYS platform were analyzed,and the impact of changes in heat pump drying system parameters on the performance of the heat pump drying system was simulated and studied.Research shows that when the air supply temperature in the drying chamber remains constant,the COP and SMER of the heat pump increase with the increase of environmental temperature;When the temperature remains constant,the heating coefficient COP decreases with the increase of the supply air temperature,while the unit energy consumption dehumidification SMER increases.In the year-round simulation,due to different environmental temperatures,the supply and return air temperatures of the drying room fluctuate greatly.In winter,the supply air temperature is basically between 40 ℃ and 50 ℃,and the supply air temperature is lower,which affects the drying efficiency.The monthly average of heat pump energy consumption,heating coefficient COP,and unit energy dehumidification SMER variables was conducted.The heat pump energy consumption was higher in winter,with a maximum of 14227.9 k J/h,and lower in summer,with a minimum of9814.3 k J/h;For the heat pump heating coefficient COP,the unit energy consumption dehumidification capacity SMER is higher in summer and lower in winter.