Author:
Wu Qiang,Zhan Zhenhui,Yang Shilin,Zhang Xianmin,Yang Lixin
Abstract
Abstract
To accurately know the working condition of the Precise Vision-based Printing Equipment (PVPE) and improve its printing accuracy and stability, this paper proposes a multi-objective ensemble of regression chains algorithm to predict the pose correction (position and orientation) errors of PVPE’s alignment platform. Since this algorithm uses XGBoost as a base learner, it’s called XGBoost Ensemble of Regressor Chain (XGB-ERC) prediction algorithm. The algorithm is verified by a test set, which is constructed based on experimental data of PVPE. The experimental result shows that the Mean Absolute Percent Error (MAPE) of this algorithm for pose correction errors x, y and θ is 6.868%, 6.495% and 5.342%, which is 25.1%, 27.6% and 16.8% higher than that of the traditional XGBoost single-objective prediction algorithm. The predicted result of the proposed algorithm can be used to compensate the correction errors of the alignment platform, which will help improve the printing accuracy and stability of PVPE, and promote the development of the field of Surface Mount Technology (SMT).
Subject
General Physics and Astronomy
Reference16 articles.
1. The management of solder paste printing machine and the impact of new technology on process quality control;Zhang;2016 China High-end SMT Academic Conference,2016
2. Error modelling and motion reliability analysis of a planar parallel manipulator with multiple uncertainties;Zhan;Mechanism and Machine Theory,2018
3. Step-by-step kinematic calibration of XY-Theta parallel platform based on visual measurement;Liang;Journal of Mechanical Engineering,2014
4. Error analysis and calibration research on correcting platform of precision solder paste printing machine;Mo;Mechanical Design,2014
5. A monocular vision system for online pose measurement of a 3RRR planar parallel manipulator;Li;Journal of Intelligent & Robotic Systems,2018
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献