| The mine ventilation system is the cornerstone of ensuring the safe production of the mine.The ability to accurately and effectively grasp the changes in the frictional resistance of the local obstacles in the mine is of great significance to the design of the underground ventilation system.This thesis mainly from static and dynamic perspectives,using computational fluid dynamics CFD software,to study the influence of local obstacles,represented by wind ducts and mine cars,on the friction resistance of roadways.Considering from the dynamic aspect,using the software of fluid mechanics,taking the five influencing factors of roadway air flow speed,tramcar running speed,blocking ratio,tramcar length and roadway length as the starting point,the relevant data of mine friction resistance when tramcar runs in the roadway are simulated.These data are sorted out as the sample of this study,the BP neural network is constructed on MATLAB software,and the predicted value is compared with the simulated value.By simulating the frictional resistance of each roadway section with different air ducts,the ratio of the section area of the air duct to the section area of the roadway is regarded as the blockage ratio of the roadway,and it is found that it has a certain relationship with the increase ratio of the frictional resistance of the mine.When the roadway blockage ratio is less than 1%,the increase rate of the mine friction resistance is less than 4.8%;when the blockage ratio is 1%-2%,the mine friction resistance increase rate is about 4.8%-9.5%;the blockage ratio is 2%-6% When the mine friction resistance increases by 9.5%-19%,When the blocking ratio is greater than 6%,the increase proportion of mine friction resistance is greater than 19%.At the same time,it is also found that no matter the position of the air duct in the tunnel is changed,or the distance between the center of the air duct and the bottom plate,the friction resistance of the mine does not change much,so the position of the air duct has little influence on the friction resistance of the mine.Can be ignored.By simulating the frictional resistance of the mine when the minecart is running,it is found that the roadway frictional resistance data obtained by CFD software simulation can be used as the data basis for constructing the neural network,and it has good universality.In the frictional resistance prediction research,the roadway frictional resistance predicted by the neural network is compared with the simulated value.The maximum absolute error is 1.1707 Pa,the maximum relative error is 12.939%,and only a few points have a relative error of more than 10%.All have reached the accuracy requirements,which proves that the neural network model can meet the prediction requirements,and can quickly and effectively determine the changes in the frictional resistance of the roadway when the transportation equipment such as mining trucks is running,with small errors,and has certain application value.Similarly,predict the measured data of the experimental roadway.The predicted value is close to the actual measured value.The maximum relative error is 11.555%,and the error range of the prediction result is within 12%.The prediction model is used to actually solve the operation of the mine car.The change of frictional resistance in the mine is feasible and can meet actual needs.The thesis has 30 pictures,23 tables,and 65 references. |
