Prediction Methods of the Warping Deformation Amount in the Fused Deposition Modeling Based on ACO-BP Algorithm
A method based on the ant colony algorithm(ACO)-error back propagation(BP)neural network algorithm was proposed for predicting the warping deformation amount in the fused deposition modeling.The initial weights and thresholds of the BP neural network were optimized by using the ACO algorithm to prevent it from converging to local minima during training.The 4-factor 4-level and 4-factor 3-level orthogonal experiments were designed as training and validation sample sets,respectively.The training sample set was used to learn the prediction model,and the validation sample set was used to verify the accuracy of the prediction method.The influences of various process parameters on warping deformation amount were analyzed using the range method.The results show that,the influences of process parameters on warping deformation amount ranged from large to small are layer height,filling rate,nozzle extrusion temperature,and printing speed.The prediction model was fully trained using a training sample set,and the prediction effect of warping deformation amount was validated using a validation sample set.The prediction accuracy was evaluated using root mean square error(RMSE),mean square error(MSE),mean absolute error(MAE),and mean absolute percentage error(MAPE).The results show that,for RMSE,the prediction accuracy of BP algorithm is approximately 1.7 times that of the ACO-BP algorithm.For MSE,the prediction accuracy of BP algorithm is approximately 2.9 times that of the ACO-BP algorithm.For MAE,the prediction accuracy of BP algorithm is approximately 1.6 times that of the ACO-BP algorithm.For MAPE,the prediction accuracy of BP algorithm is approximately 2.2 times that of the ACO-BP algorithm.The BP neural network optimized by the ACO algorithm has a higher prediction accuracy.
Ant Colony Algorithm-Error Back Propagation Neural Network AlgorithmFused Deposition ModelingWarping Deformation AmountPrediction Method
万方数据
维普
