煤矿掘进机自定位截割控制方法及试验研究
Self-positioning Cutting Control Methods and Experimental Research for Coal Mine Roadheaders
刘送永 1吴洪状 2程诚 2宋明江 3崔玉明4
作者信息
- 1. 中国矿业大学机电工程学院,徐州,221116
- 2. 苏州大学未来科学与工程学院,苏州,215222
- 3. 中国矿业大学机电工程学院,徐州,221116;中国煤炭科工集团太原研究院有限公司,太原,030006
- 4. 江苏师范大学机电工程学院,徐州,221116
- 折叠
摘要
开展了掘进机自定位截割控制方法及试验研究,提出了掘进机自定位截割控制策略,使用基于单目视觉与深度学习的掘进机机体六自由度位姿检测方法,以及具有规定性能的双层模糊自适应反步控制方法实现了掘进机自定位截割,并将其用于机体任意位姿下的截割头循迹跟踪控制.在掘进机两种不同的机体位姿下进行了截割头循迹跟踪控制试验,试验结果显示最大轮廓误差分别在48 mm和52 mm(约2.14％与2.32％)以内,验证了提出的掘进机自定位截割控制方法的有效性.
Abstract
A self-positioning cutting control methods were proposed,and the experimental studies of roadheaders were conducted herein.An self-positioning cutting control strategy was proposed.The monocular vision and deep learning based six degrees of freedom pose detection method for roadheader body and the double-layer fuzzy adaptive backstepping control method with prescribed performance were utilized to achieve the self-positioning cutting of roadheaders.The tracking control of cutting head was realized at arbitrary body poses of the roadheaders.The cutting head tracking control experi-ments were carried out under two different body poses of the roadheaders.The experimental results il-lustrate that the maximum contour errors are within 48 mm and 52 mm(about 2.14％and 2.32％)re-spectively,which verifies the effectiveness of the proposed self-positioning cutting control method for the roadheaders.
关键词
巷道掘进机/位姿检测/轨迹跟踪控制/自定位截割Key words
roadheader/pose detection/trajectory tracking control/self-positioning cutting引用本文复制引用
基金项目
江苏省杰出青年基金(BK20211531)
徐州市重点研发计划(KC22404)
江苏省产学研合作项目(BY20230191)
江苏师范大学博士学位教师科研支持项目(22XFRS011)
出版年
2024
国家科技期刊平台
NSTL
万方数据