钻具输送装置非线性动力学分析及稳定性控制  

Nonlinear dynamic analysis and stability control of drilling tool conveying mechanism

作　　者：于萍 穆特 朱黎辉 周子业 宋杰 YU Ping;MU Te;ZHU Li-hui;ZHOU Zi-ye;SONG Jie(College of Mechanical and Aerospace Engineering,Jilin University,Changchun 130022,China)

机构地区：[1]吉林大学机械与航空航天工程学院,长春130022

出　　处：《吉林大学学报（工学版）》2021年第3期820-830,共11页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家深部探测技术与实验研究专项项目(sinoprobe-09);吉林省科技发展计划项目(20170101204JC)。

摘　　要：钻具输送装置为刚柔耦合多体系统,工作时由于系统参数和外部扰动的不确定,使其工作稳定性下降。针对这一问题,利用多体系统传递矩阵法建立了钻具输送装置非线性动力学模型,依据工作要求设定了轨迹函数。将钻具输送装置的工作稳定性控制分为工作位姿跟踪控制和装置内柔性体非线性振动抑制两部分。提出了基于BP神经网络的PID控制算法,对整机位姿进行动态跟踪控制;对于柔性体的振动,采用将压电材料粘贴于柔性构件表面形成智能复合材料,并利用基于模糊RBF神经网络的滑模控制算法进行抑制。仿真结果显示,整机的工作位置精度得到了显著提高,柔性体振动得到了有效抑制。The drilling tool conveying mechanism is a rigid-flexible coupling multibody system.Due to the uncertainty of system parameters and external disturbances during operation,its working stability is reduced.To solve this problem,a nonlinear dynamic model of the drilling tool conveying mechanism was established using the multibody system transfer matrix method,and a trajectory function was set according to the work requirements.The working stability control of the drilling tool conveying mechanism is divided into two parts:working position and attitude tracking control and nonlinear vibration suppression of the flexible body in the mechanism.A PID control algorithm based on BP neural network is proposed to dynamically track the posture of the whole mechanism.For the vibration of the flexible body,a piezoelectric material is pasted on the surface of the flexible member to form an intelligent composite material,and the sliding mode control algorithm based on fuzzy RBF neural network is used for suppression.The simulation results show that the working position accuracy of the whole mechanism is significantly improved,and the vibration of the flexible body is effectively suppressed.

关 键 词：机械电子工程 非线性动力学 强迫振动 稳定性控制 

分 类 号：TE928[石油与天然气工程—石油机械设备]