Temperature Field Prediction And Control Of Grain Storage Ventilation Process Based On Intelligent Algorithm

The safe storage of grain is related to the national economy,people's livelihood and national security,and mechanical ventilation is an important technology to maintain the quality of grain and to improve the environment of grain storage,which plays a very important role in the safe storage of grain in China.In the process of mechanical ventilation,due to the constant change of grain heap temperature,the ventilation timing cannot be accurately determined,resulting in high ventilation energy consumption,and even the occurrence of harmful phenomena such as grain heap condensation.Therefore,it is of great significance to predicate and control of the temperature field in mechanical ventilation process.This thesis aims to study the change and control methods of the grain heap temperature in the process of ventilation.The prediction model of grain heap temperature in mechanical ventilation process is established based on the intelligent algorithm,and the quantitative control methods of grain heap temperature is proposed.The main contents of the thesis are as follows:(1)Based on investigation and literature search,the main influencing factors of grain heap temperature in mechanical ventilation process are: external temperature,external humidity,temperature inside the grain bin,humidity inside the grain bin,air vents' wind speed,air vents' temperature and air vents' humidity,and evaluation index of grain heap temperature;(2)In order to reflect the actual situation of grain heap temperature,the experimental grain heap is divided into layers,and the prediction model of maximum temperature in each layer of grain heap is established based on the random forest algorithm,support vector machine(SVM)algorithm,neural network algorithm.The validity and the reliability of the model is verified by experimental data,and at the same time,the prediction results of the three models are analyzed.The results show that the random forest prediction model has the highest accuracy and the best fitting effect,which can be applied to the grain heap temperature control research;(3)Based on the importance analysis of the influencing factors of the maximum grain heap temperature with the random forest prediction model,the importance order of the influencing factors are obtained.They are: humidity inside the grain bin,external temperature,air vents' temperature,temperature inside the grain bin,air vents' humidity,air vents' wind speed,and external humidity.In the process of granary mechanical ventilation,the factors with greater importance deserves more attention according to the key factors importance order.It provides a certain reference to grasp the best mechanical ventilation opportunity and improve the ventilation effect;(4)Take a practical grain bin with certain basic conditions as an example,the relationship between the vents wind speed and the vents temperature and the maximum temperature of the grain heap is obtained by changing manageable factors while other influencing factors remain unchanged.The critical points of the highest temperature of grain heap in low temperature condition was calculated by graphic method.It shows that the temperature of the grain heap can be controlled by selecting the test point that below the critical points,which also provides a reference for scientific storage and ventilation.