摘要
在陆地钻井中,陆地钻柱输送机器人可以自动完成从钻柱抓取、调姿、输送到鼠洞的过程。但是钻柱在放置过程中会产生倾斜,导致机器人抓取失败。因此本文设计基于激光传感器的钻柱输送自动纠偏算法。首先,采用两个激光传感器扫描并获取钻柱任意两处切面距离信息,利用最小二乘法拟合得到切面圆心位置。由于实际现场作业时,钻柱表面粘附泥土将会影响采集的数据,采用格拉布斯准则通过多次迭代进行数据筛选。然后通过圆心位置计算出钻柱偏转角度并发送给机械手,以便进行定位抓取。最后模拟钻井现场中钻柱附着泥土的位置和厚度不同,进行了算法有效性实验。实验结果表明,该算法切实可行,工程可移植性高,满足工程应用要求,提高了钻柱输送机器人的自动化水平。
In land drilling,the land drill column conveying robot can automatically grab drill columns,adjust the attitude of drill columns,and then transport drill columns to the rat hole.However,drill columns may be inclined when placed,causing the robot to fail to grasp.Therefore,this paper designs an automatic deviation correction algorithm for drill column transportation based on laser sensors.Firstly,two laser sensors are used to scan and acquire the distance information of any two sections of the drill column,and the position of the center of the section is obtained by least square fitting.Due to the fact that the soil adhered to the surface of drill strings will affect the collected data during actual field operations,the Grubbs criterion is used to screen the data through multiple iterations.Then,the deflection angle of the drill string is calculated by the center of the circle and sent to the manipulator for positioning and grabbing.Finally,the effectiveness of the algorithm is tested by simulating the different positions and thicknesses of the soil attached to the drill string in the drilling site.The experimental results show that the algorithm is feasible,highly portable in engineering,meets the requirements of engineering application,and improves the automation level of drill string conveying robots.
作者
臧日高
张春堂
樊春玲
Zang Rigao;Zhang Chuntang;Fan Chunling(College of Automation and Electronic Engineering,Qingdao University of Science and Technology,Qingdao 266061,China)
出处
《电子测量技术》
北大核心
2023年第5期30-37,共8页
Electronic Measurement Technology
基金
山东省自然科学基金(ZR2019MEE071)项目资助
关键词
钻柱输送机器人
钻柱中心识别
格拉布斯准则
自动纠偏
drill column conveying robot
drill column center identification
Grubbs criterion
attitude correction
作者简介
臧日高,硕士研究生,主要研究方向为检测技术与自动化装置。E-mail:rigao_zang@163.com;通信作者:张春堂,副教授,硕士生导师,主要研究方向为智能检测技术及开发、机器视觉、嵌入式系统、人工智能技术的研究和应用。E-mail:zct1999@163.com;樊春玲,博士,教授,硕士生导师,主要研究方向为多相流传感与流体流动,机器视觉和信息处理。
