Title :
Fault prediction of the CNC machine tool servo system based on the BRB
Author :
Bangcheng Zhang ; Xiaojing Yin ; Yilong Wang ; Bing Zhang ; Zhijie Zhou
Author_Institution :
Changchun Univ. of Technol., Changchun, China
Abstract :
In order to achieve optimal maintenance and Prediction and Health Management (PHM) of CNC (Computer Numerical Control) machine tool, a belief rule base (BRB) is proposed to predict the fault of the servo system by studying the key techniques of fault prediction. Based on the analysis of fault mechanism in CNC machine tool servo system, a BRB based fault prognosis model of the servo system is established by combing expert knowledge with quantitative information. Moreover, the evidential reasoning (ER) algorithm is used to achieve fault on-line prediction. Experimental results show that the proposed method can accurately reflect the behavior of the system and take full use of uncertain information to improve the accuracy of fault prediction.
Keywords :
belief networks; computerised numerical control; condition monitoring; control engineering computing; fault diagnosis; inference mechanisms; machine tools; maintenance engineering; production engineering computing; servomechanisms; BRB based fault prognosis model; CNC machine tool servo system; ER algorithm; PHM; belief rule base; computer numerical control machine tool; evidential reasoning; expert knowledge; fault mechanism; fault online prediction; optimal maintenance; prediction and health management; system behavior; Accuracy; Computer numerical control; Machine tools; Predictive models; Prognostics and health management; Servomotors; Vibrations; Belief rule base (BRB); CNC machine tool; Fault prediction; Servo system;
Conference_Titel :
Prognostics and System Health Management Conference (PHM-2014 Hunan), 2014
Conference_Location :
Zhangiiaijie
Print_ISBN :
978-1-4799-7957-8
DOI :
10.1109/PHM.2014.6988151