Key Parameter Analysis of Die-casting Light Alloy Based on Machine Learning
"Parameters-Offline quality"big database was established by collecting the data from the die-casting produc-tion line of forward engine room of new energy vehicles.Then,four types of machine learning models were used to train the dataset.The results indicate that the bagged decision trees model has the satisfied prediction accuracy and gen-eralization ability,and the tolerated accuracy of prediction results of the test dataset reaches 77.3%.Furthermore,the influences of key parameters on the quality of castings were ranked by calculating the relative influences and sensitivity levels,which has important guiding significance in optimizing and controlling of pressure die-casting parameters.
Machine LearningData DrivenBagged Decision Trees ModelKey ParametersLight Alloys
NETL
NSTL
万方数据
