Fatigue Life Analysis And Prediction Of Planetary Mechanism In Shearer Cutting Part

The planetary mechanism is the key part of the shearer cutting part.The coal seam occurrence condition,the kinematics parameters of the shearer and the structural characteristics of each part have a direct influence on its fatigue life.To analyze and predict the fatigue life of the key parts of the planetary mechanism of the shearer cutting part,a three-dimensional solid model of the cutting part of the MG2*55/250-BW shearer is constructed by using the Pro/E,the rigid-flexible coupling dynamic simulation model of cutting part is constructed by using ANSYS and ADAMS.The maximum stress value of key parts of cutting part planetary mechanism is obtained and used as input.The fatigue life and damage value of planet carrier and planet shaft are obtained by n Soft,and the weak link is found.Discussed the impact of the gangue ruggedness coefficient f,traction speed v,drum speed n and cutting depth B on the fatigue life.The BP?PSO-BP and improved PSO-BP are used to predict the life of planet carrier under different working conditions.The results show that,under the conditions of coal firmness factor is 1.4,the firmness coefficient of the gangue is 8.4,the traction speed is 2.5m/min,the rotation speed is 90r/min,and the cutting depth is 600 mm,the maximum stress of planet carrier and planet shaft are 554.7812 MPa and 411.5875 MPa,respectively the stress concentration area is at the spline retrogression groove of planet carrier and the shaft shoulder of planet shaft,the fatigue life is 5.5072 e6 and 1.1373 e8;respectively aimed at cutting-coal loading performance of shearer,constructing the model of co-control of traction speed and drum speed of shearer,in the cooperative speed control model,the error calculation module of recommended traction speed and actual working traction speed and the error calculation module of recommended speed and actual working speed are close to 0,it is proved that this system can realize cooperative speed regulation of shearer,and work on that n-v,can improve the performance of shearer and fatigue life of key parts;BP,PSO-BP and improved PSO-BP three neural network models,the maximum relative error in predicting fatigue life is 4.61%,2.79%and 1.02%,the number of iterations is 25,8 and 6,improved PSO-BP model improves prediction accuracy,also improves the iteration speed.The integration of Pro/E,ANSYS,ADAMS,n Soft and improved PSO-BPNN provides a new method for the fatigue life prediction of key parts of industrial and mining equipment.The paper has 59 pictures,16 tables and 84 references.