Health Status Evaluation of Welding Robots Based on the Evidential Reasoning Rule

被引:2
|
作者
Zhang, Bang-Cheng [1 ,2 ]
Wang, Ji-Dong [1 ]
Gao, Shuo [1 ]
Yin, Xiao-Jing [1 ]
Gao, Zhi [1 ]
机构
[1] Changchun Univ Technol, Sch Mech & Elect Engn, Changchun 130103, Peoples R China
[2] Changchun Inst Technol, Sch Mech & Elect Engn, Changchun 130103, Peoples R China
关键词
welding robot; health status evaluation; evidential reasoning rule; CMA-ES algorithm; PERFORMANCE EVALUATION;
D O I
10.3390/electronics12081755
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
It is extremely important to monitor the health status of welding robots for the safe and stable operation of a body-in-white (BIW) welding production line. In the actual production process, the robot degradation rate is slow and the effective data are poor, which can reflect a degradation state in the large amount of obtained monitoring data, which causes difficulties in health status evaluation. In order to realize the accurate evaluation of the health status of welding robots, this paper proposes a health status evaluation method based on the evidential reasoning (ER) rule, which reflects the health status of welding robots by using the running state data monitored in actual engineering and through the qualitative knowledge of experts, which makes up for the lack of effective data. In the ER rule evaluation model, the covariance matrix adaptive evolutionary strategy (CMA-ES) algorithm is used to optimize the initial parameters of the evaluation model, which improved the accuracy of health status evaluations. Finally, a BIW welding robot was taken as an example for verification. The results show that the proposed model is able to accurately estimate the health status of the welding robot by using the monitored degradation data.
引用
收藏
页数:12
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