Short-Term Relay Quality Prediction Algorithm Based on Long and Short-Term Memory

作     者：XUE Wendong CHAI Yuan LI Qigan HONG Yongqiang ZHENG Gaofeng 

作者机构：Department of Instrumental and Electrical EngineeringXiamen University 

出 版 物：《Instrumentation》 (仪器仪表学报（英文版）)

年 卷 期：2018年第5卷第4期

页      面：46-54页

学科分类：12[管理学] 080801[工学-电机与电器] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0808[工学-电气工程] 08[工学] 081104[工学-模式识别与智能系统] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：funded by Fujian Science and Technology Key Project(No.2016H6022 2018J01099 2017H0037) 

主　　题：Relay Production Line Long and Short-Term Memory Network Keras Deep Learning Framework Quality Prediction 

摘      要：The fraction defective of semi-finished products is predicted to optimize the process of relay production lines, by which production quality and productivity are increased, and the costs are decreased. The process parameters of relay production lines are studied based on the long-and-short-term memory network. Then, the Keras deep learning framework is utilized to build up a short-term relay quality prediction algorithm for the semi-finished product. A simulation model is used to study prediction algorithm. The simulation results show that the average prediction absolute error of the fraction is less than 5%. This work displays great application potential in the relay production lines.