Machining Quality Prediction of Marine Diesel Engine Block Based on Error Transmission Network

Abstract

In view of the high precision requirement of the marine diesel engine body and the difficulty of quality control, a quality prediction method of the body, based on a process error transfer network, is proposed. First, according to the processing information of the body, the network nodes and edges are abstracted to establish the process error transfer network of the body. Then, the key quality control points and key quality features of the diesel engine body are determined by the PageRank and node degree. The key quality features obtained from the network analysis are taken as the output, and the corresponding process errors and process parameters are taken as the input. Finally, the quality prediction model of the body is established based on SVR algorithm, and the C, g parameters of SVR algorithm are optimized by the K-fold cross-validation method and grid search method to improve the prediction accuracy of the body processing quality.