Research on control system of drill pipe conveying device based on fuzzy particle swarm optimization

Authors

ZHANG Ning, CCTEG Xi’an Research Institute (Group) Co., Ltd., Xi’an 710077, ChinaFollow
LIU Qi, CCTEG Xi’an Research Institute (Group) Co., Ltd., Xi’an 710077, China
SHAO Junjie, CCTEG Xi’an Research Institute (Group) Co., Ltd., Xi’an 710077, China
CHANG Jianghua, CCTEG Xi’an Research Institute (Group) Co., Ltd., Xi’an 710077, China
LUO Pengping, CCTEG Xi’an Research Institute (Group) Co., Ltd., Xi’an 710077, China
ZOU Zujie, CCTEG Xi’an Research Institute (Group) Co., Ltd., Xi’an 710077, China

Abstract

In the tripping operation of large-diameter rescue well construction, the drill pipe conveying device used for large-diameter drilling tool transportation and drill string connection. In view of the problem that it is difficult to quickly and accurately lift the drill pipe to the angle of power head for make-up due to its easy vibration in the process of positioning, the structural characteristics and working principle of the drill pipe conveying device were analyzed at first. The kinematic model for the lifting of drill pipe was deduced with the structural relationship, obtaining the mapping relationship in the motion law of the drill pipe end joint, lifting cylinder and transport trolley. Meanwhile, the dynamic load model for the lifting of drill pipe was established using the finite element method. Thus, it was found that the vibration acceleration of the drill pipe end joint was mainly determined by the working speed of the lifting cylinder and the transport trolley, while the working speed of each component was mainly determined by the respective input flow. Besides, the comprehensive error evaluation function based on particle swarm optimization algorithm was introduced. Then, the comprehensive error and acceleration error were calculated using the weighted method with the rotation angle error and position error of the drill pipe end joint as the input signals. At the same time, the fuzzy control rules were established using the trapezoidal membership function, and thus the relationship of the comprehensive error and acceleration error with the proportional parameter, integral parameter and differential parameter was obtained, to complete the adjustment of PID control parameters, thereby realizing the active vibration suppression control of the drill pipe end joint. Finally, the numerical simulation model was built with MATLAB software. Specifically, simulation research was performed based on the measured data signal of a drill pipe conveying device during its operation. It is shown that the comprehensive error of system could attenuate the amplitude to less than 10% of the peak value within 0.9 s only at the acceleration error of 0.05 mm/s², which is verified by the field application test. According to the test results, the control method of the drill pipe conveying device could realize the active vibration suppression of drill pipe during the transportation, so that the drill pipe end joint could be stabilized in a short time during the positioning process. The average time for the loading/unloading of a single drill pipe is about 192.8 s if the fuzzy controller is used, saving about 60 s, and the overall efficiency of drill pipe loading/unloading is improved by 24%. In general, the research results could provide a theoretical basis for improving the overall construction safety and efficiency of the drill pipe conveying device.

Keywords

drill pipe conveying device, kinematic analysis, particle swarm optimization algorithm, optimization iteration, fuzzy control

DOI

10.12363/issn.1001-1986.22.05.0432

Recommended Citation

ZHANG Ning, LIU Qi, SHAO Junjie, et al. (2023) "Research on control system of drill pipe conveying device based on fuzzy particle swarm optimization," Coal Geology & Exploration: Vol. 51: Iss. 3, Article 62.
DOI: 10.12363/issn.1001-1986.22.05.0432
Available at: https://cge.researchcommons.org/journal/vol51/iss3/62

Reference

[1] 田宏亮,邹祖杰,郝世俊,等. 矿山灾害生命保障救援通道快速安全构建关键技术与装备[J]. 煤田地质与勘探,2022,50(11):1−13.

TIAN Hongliang,ZOU Zujie,HAO Shijun,et al. Key technologies and equipment of quickly and safely building life support and rescue channel in mine disaster[J]. Coal Geology & Exploration,2022,50(11):1−13.

[2] 张彪,康玉国,黄勇,等. 矿山救援地面生命保障孔高效成孔关键技术[J]. 煤田地质与勘探,2022,50(11):14−23.

ZHANG Biao,KANG Yuguo,HUANG Yong,et al. Key technologies of surface efficient life support hole forming for mine rescue[J]. Coal Geology & Exploration,2022,50(11):14−23.

[3] 渠伟,李新年,张堃,等. 大口径救援生命通道的施工工艺及钻具配置[J]. 中国安全生产科学技术,2016,12(增刊1):44−48.

QU Wei,LI Xinnian,ZHANG Kun,et al. Construction technology and drilling tools configuration of large diameter life rescue channel[J]. Journal of Safety Science and Technology,2016,12(Sup.1):44−48.

[4] 凡东. ZMK5530TZJ100型车载钻机的试验研究[J]. 煤田地质与勘探,2018,46(2):201−204.

FAN Dong. Test research on ZMK5530TZJ100 truck–mounted drilling rig[J]. Coal Geology & Exploration,2018,46(2):201−204.

[5] 徐俏武,张小新. 液压动力猫道钻杆减阻控制优化研究[J]. 制造业自动化,2021,43(11):144−147.

XU Qiaowu,ZHANG Xiaoxin. Optimization of hydraulic power catwalk drill pipe drag reduction control system[J]. Manufacturing Automation,2021,43(11):144−147.

[6] 康思杰,于萍,靳恩朝,等. 全液压自动猫道举升系统控制策略研究[J]. 机床与液压,2016,44(3):102−105.

KANG Sijie,YU Ping,JIN Enchao,et al. Control strategy for lifting system of hydraulic automatic catwalk[J]. Machine Tool & Hydraulics,2016,44(3):102−105.

[7] 李扬,侯加林,苑进,等. 基于改进PSO的模糊PID高枝修剪机械臂末端抑振算法与试验[J]. 农业工程学报,2017,33(10):49−58.

LI Yang,HOU Jialin,YUAN Jin,et al. Experiment and vibration suppression algorithm for high–branch pruning manipulator based on fuzzy PID with improved PSO[J]. Transactions of the Chinese Society of Agricultural Engineering,2017,33(10):49−58.

[8] 娄军强,魏燕定,李国平,等. 基于遗传优化算法的柔性机械臂抑振轨迹规划研究[J]. 振动与冲击,2016,35(11):1−6.

LOU Junqiang,WEI Yanding,LI Guoping,et al. Optimal trajectory planning of a flexible manipulator for its vibration suppression using genetic algorithm[J]. Journal of Vibration and Shock,2016,35(11):1−6.

[9] 黄毅,鄂加强,郭岗,等. 变姿态柔性机械臂横向振动主动控制理论与实验[J]. 天津大学学报(自然科学与工程技术版),2016,49(7):716−720.

HUANG Yi,E Jiaqiang,GUO Gang,et al. Theoretical and experimental study on active control of transverse vibration of flexible manipulator in time–varying postures[J]. Journal of Tianjin University(Science and Technology),2016,49(7):716−720.

[10] 张幼振,刘焱杰,钟自成. 预钻式原位岩体剪切测量系统研制与试验分析[J]. 煤田地质与勘探,2022,50(2):156−162.

ZHANG Youzhen,LIU Yanjie,ZHONG Zicheng. Development and test analysis of borehole in-situ rock mass shear measurement system[J]. Coal Geology & Exploration,2022,50(2):156−162.

[11] 李国利,姬长英,顾宝兴,等. 多末端苹果采摘机器人机械手运动学分析与试验[J]. 农业机械学报,2016,47(12):14−21.

LI Guoli,JI Changying,GU Baoxing,et al. Kinematics analysis and experiment of apple harvesting robot manipulator with multiple end–effectors[J]. Transactions of the Chinese Society of Agricultural Machinery,2016,47(12):14−21.

[12] 马如奇,姜水清,刘宾,等. 月球采样机械臂系统设计及试验验证[J]. 宇航学报,2018,39(12):1315−1322.

MA Ruqi,JIANG Shuiqing,LIU Bin,et al. Design and verification of a lunar sampling manipulator system[J]. Journal of Astronautics,2018,39(12):1315−1322.

[13] 张建华,许晓林,刘璇,等. 双臂协调机器人相对动力学建模[J]. 机械工程学报,2019,55(3):34−42.

ZHANG Jianhua,XU Xiaolin,LIU Xuan,et al. Relative dynamic modeling of dual–arm coordination robot[J]. Journal of Mechanical Engineering,2019,55(3):34−42.

[14] 张幼振,张宁,张献振. PDC锚杆钻头回转钻进的力学特性与试验[J]. 煤田地质与勘探,2019,47(2):207−211.

ZHANG Youzhen,ZHANG Ning,ZHANG Xianzhen. Mechanical characteristics and test of rotary drilling of PDC anchor bit[J]. Coal Geology & Exploration,2019,47(2):207−211.

[15] 李连鹏,解仑,刘振宗,等. 基于人机交互的重载机械臂控制方法[J]. 机器人,2018,40(4):525−533.

LI Lianpeng,XIE Lun,LIU Zhenzong,et al. A control method for heavy load manipulator based on human–machine interaction[J]. Robot,2018,40(4):525−533.

[16] 豆旭谦,姚宁平,李秀山,等. 基于单柱齿破岩过程的高压液动冲击回转钻进试验研究[J]. 煤田地质与勘探,2022,50(12):170−176.

DOU Xuqian,YAO Ningping,LI Xiushan,et al. Experimental study on high-pressure hydraulic percussive rotary drilling based on single-tooth rock-breaking process[J]. Coal Geology & Exploration,2022,50(12):170−176.

[17] 洪博,董泽. PID参数优化方法对优化效果的影响研究[J]. 计算机仿真,2015,32(2):391−394.

HONG Bo,DONG Ze. Study of an effect of PID parameter optimization methods on optimization effect[J]. Computer Simulation,2015,32(2):391−394.

[18] 刘董,李京慧,迟宗涛,等. 基于模糊PID控制的控温箱设计[J]. 传感器与微系统,2021,40(3):73−76.

LIU Dong,LI Jinghui,CHI Zongtao,et al. Design of incubator based on fuzzy PID control[J]. Transducer and Microsystem Technologies,2021,40(3):73−76.

[19] 冯茜,李擎,全威,等. 多目标粒子群优化算法研究综述[J]. 工程科学学报,2021,43(6):745−753.

FENG Qian,LI Qing,QUAN Wei,et al. Overview of multiobjective particle swarm optimization algorithm[J]. Chinese Journal of Engineering,2021,43(6):745−753.

[20] 徐利锋,黄祖胜,杨中柱,等. 引入多级扰动的混合型粒子群优化算法[J]. 软件学报,2019,30(6):1835−1852.

XU Lifeng,HUANG Zusheng,YANG Zhongzhu,et al. Mixed particle swarm optimization algorithm with multistage disturbances[J]. Journal of Software,2019,30(6):1835−1852.

[21] 孟庆宽,仇瑞承,张漫,等. 基于改进粒子群优化模糊控制的农业车辆导航系统[J]. 农业机械学报,2015,46(3):29−36.

MENG Qingkuan,QIU Ruicheng,ZHANG Man,et al. Navigation system of agricultural vehicle based on fuzzy logic controller with improved particle swarm optimization algorithm[J]. Transactions of the Chinese Society of Agricultural Machinery,2015,46(3):29−36.

[22] 徐偲喆,查晓锐. 基于改进粒子群优化模糊控制的MPPT算法研究[J]. 电机与控制应用,2019,46(10):35−39.

XU Sizhe,ZHA Xiaorui. Research on MPPT algorithm based on improved particle swarm optimization fuzzy control[J]. Electric Machines and Control Application,2019,46(10):35−39.

[23] 刘若君,张幼振,姚克. 基于T-S模糊故障树的煤矿坑道钻机液压动力系统故障诊断研究[J]. 煤田地质与勘探,2022,50(12):194−202.

LIU Ruojun,ZHANG Youzhen,YAO Ke. Fault diagnosis of hydraulic power system for coal mine tunnel drilling rig based on T-S fuzzy fault tree[J]. Coal Geology & Exploration,2022,50(12):194−202.