中国机械工程2026，Vol.37Issue(4)：939-947,958,10.DOI:10.3969/j.issn.1004-132X.2026.04.018
高负载动态工况下工业机器人的能耗预测
Energy Consumption Prediction of Industrial Robots under High-load Dynamic Conditions
摘要
Abstract
The power of industrial robots under high-load and highly fluctuating processing conditions showed non-stationary and multi-source coupling characteristics,which led to the problems of reduced ac-curacy and stability of energy consumption prediction models under cross-operation conditions.Multi-source time series data were collected from the self-built processing experimental platform.The heteroge-neous data were synchronized and resampled through timestamps,and power tags were constructed using sliding windows.The prediction results of random forest,gradient boosting tree,support vector regres-sion,multi-layer perceptive machine and two fusion structure models under multiple working conditions were compared.The results show that the energy consumption prediction result of the gradient boosting tree+support vector regression fusion model is the best in the working conditions without participation in training,with an average absolute error of 3.73%.The research reveales the predictive characteristics of dif-ferent models under high-dynamic processing conditions,which may provide technical support for energy effi-ciency modeling,process optimization and green operations of high-load processing of the industrial robots.关键词
工业机器人/高负载加工/能量消耗/数据驱动/融合模型Key words
industrial robot/high-load processing/energy consumption/data-driven/fusion model分类
信息技术与安全科学引用本文复制引用
孙悦,黄辉,尹方辰..高负载动态工况下工业机器人的能耗预测[J].中国机械工程,2026,37(4):939-947,958,10.基金项目
福建省科技重大专项(2024HZ025008) （2024HZ025008）
第七批泉州市引进高层次人才团队项目(2024CT005) （2024CT005）
国家自然科学基金(52575495) （52575495）
黑龙江省基本科研业务费(2020-KYYWF-0225) （2020-KYYWF-0225）
