基于改进PSO-BP的采煤机截割部行星架疲劳寿命分析及预测

FATIGUE LIFE ANALYSIS AND PREDICTION OF PLANET CARRIER IN CUTTING PART OF SHEARER BASED ON IMPROVED PSO-BP

为对采煤机截割部行星架进行疲劳寿命分析及预测,建立采煤机的刚柔耦合模型,研究了行星架的动力学特性,得到了其最大应力值并以此作为输入,利用n Soft得到了行星架的疲劳寿命,利用BP、PSO-BP和改进的PSO-BP对不同工况下的行星架寿命进行预测。研究表明:夹矸坚固性系数为8.4,截深600 mm,转速90 r/min,牵引速度2.5 m/min的工况下,行星架的最大应力为554.7812 MPa,应力集中区域为花键退刀槽处,疲劳寿命为5.5072×10^(6);BP、PSO-BP和改进的PSO-BP三种神经网络模型中,预测疲劳寿命最大相对误差分别为4.35%、2.52%和0.90%,迭代次数分别为23、8和6次,改进PSO-BP模型既提高了预测精度,也提高了迭代速度。融合Matlab、Ansys、Adams、n Soft和改进的PSOBPNN,为工矿装备关键零件的疲劳寿命预测提供了方法。

In order to analyze and predict the fatigue life of the shearer’s cutting planet carrier,the shearer’s rigid-flexible coupling model was established,the planet carrier’s dynamic characteristics was studied,and the planet carrier’s maximum stress value was obtained as the input.The planet carrier’s fatigue life was obtained by using n Soft,and the planet carrier’s fatigue life,under different working conditions was predicted by using BP,PSO-BP and improved PSO-BP.The results show that under the condition of solidity coefficient of 8.4,depth of cut-off 600 mm,rotational speed of 90 r/min and traction speed of 2.5 m/min,the maximum stress is 554.78 MPa,the planet carrier’s stress concentration area is at the spline receding groove,and the fatigue life is 5.5072×10^(6).Among the three neural network models,BP,PSO-BP and the improved PSO-BP,the predicted fatigue life’s maximum relative error is 4.35%,2.52%and 0.90%,and the iteration’s number is 23,8 and 6 times,respectively.The improved PSO-BPNN model improves the prediction accuracy and also improves the iterative speed.Combining MATLAB、ANSYS、ADAMS、n Soft and improved PSO-BPNN,this paper provides a method for predicting the fatigue life of key parts of industrial and mining equipment.