工业机器人整机性能影响因素及评估模型优化  

Optimization of Influencing Factors and Evaluation Model forIndustrial Robot Performance

作　　者：李本旺 何国田 窦满义 甘雷 王松 高路刚 黄云峰[1] Li Benwang;He Guotian;Dou Manyi;Gan Lei;Wang Song;Gao Lugang;Huang Yunfeng(Chongqing University,Chongqing 400044,China;不详)

机构地区：[1]重庆大学高端装备机械传动全国重点实验室,重庆市400044 [2]中科院重庆绿色智能技术研究院 [3]中国科学院大学重庆学院 [4]重庆凯瑞机器人技术有限公司

出　　处：《工具技术》2024年第12期77-85,共9页Tool Engineering

基　　金：国家重点研发计划项目资助(2022YFB4702100)。

摘　　要：工业机器人整机性能的综合评估涉及核心零部件、工况条件与环境因素等输入条件和准确度、重复性与超调量等输出条件,待评估参数众多且各因素之间存在复杂的耦合关系,理论建模方式存在无法统一表征或表征不全面等问题。数据驱动建模对大量的试验数据信息进行挖掘,综合考虑输入中所包含的各种因素对机器人整机性能的影响,能够较为准确地反映输入输出间的映射关系。本研究结合理论分析手段,把控各影响因素对机器人整机性能的总体影响趋势与输入输出间的理论分布关系,并将分析结果用于指导数据驱动建模,最终建立工业机器人整机性能综合评估模型。In this paper,mainly for industrial robot performance of comprehensive assessment involves the core components,working conditions and environmental factors such as input conditions and accuracy,repeatability and overshoot of output condition,for evaluating parameters of many factors and complex coupling relationship between,theoretical modeling has such problems as not unified property or not comprehensive.Data-driven modeling can reflect the mapping relationship between input and output more accurately by mining a large number of experimental data and integrating the influence of various factors contained in the input on the performance of the robot.Combined with theoretical analysis methods,this study will control the overall influence trend of various influencing factors on the overall performance of the robot and the theoretical distribution relationship between the input and output,and the analysis results will be used to guide the data-driven modeling,and the comprehensive assessment model of the overall performance of the industrial robot is established.

关 键 词：工业机器人 准确度 数据驱动 评估模型 

分 类 号：TG68[金属学及工艺—金属切削加工及机床] TH128[机械工程—机械设计及理论]