Stiffness modeling and optimization of a 3-DOF parallel robot in a serial-parallel polishing machine

Xu, Peng; Li, Bing; Cheung, Chi Fai; Zhang, Jufan

doi:10.1007/s12541-017-0060-1

Cited by 35 publications

(8 citation statements)

References 37 publications

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“…The deviation correction mechanism can be regarded as a series mechanism in which the deviation-correction roller is connected in series through the connecting rod, the slider board and the connection plate along the centerline. The more components connected in series, the smaller the stiffness is [11]. Therefore, the stiffness relationship of A, B and C is K A ＜K B ＜K C .…”

Section: Establishment Of Finite Element Model Of the Deviation Corre...mentioning

confidence: 99%

Research on transient displacement response of the deviation correction mechanism of lithium-ion battery high-speed winding machine

Xia¹,

Lin²,

Yu³

et al. 2023

3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023)

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Aiming at the common problem in the industry that response of the deviation correction mechanism of lithium-ion battery winding machine is not timely under the high-speed winding state of 3.5m/s, a theoretical dynamics model for displacement response of deviation correction mechanism of the lithium-ion battery high-speed winding machine based on lumped parameter method was established; the transient displacement response and error rate of the transient displacement response of the correction mechanism were analyzed, and the relationship between transient displacement response and the displacement input and the relationship between error rate of the transient displacement response and the displacement input were obtained. A finite element model of the transient displacement response of the deviation correction mechanism was established based on Ansys software, and the transient dynamic simulation of the deviation correction mechanism was carried out. An improved scheme was proposed to shorten the distance between motor and deviation correction roller, and change the deviation correction mechanism in series along the axis direction of the motor into a parallel arrangement. The effectiveness of the improved mechanism was verified through the high-speed winding test with winding rate of 3.5m/s. The results show that the main influencing factor of the transient displacement response of the deviation correction mechanism is overall stiffness. The time required to correct the deviation of the improved deviation correction mechanism is reduced by 38.6%. The proportion of pole pieces exceeding the allowable range of 0.2mm~0.8mm due to untimely deviation correction decreased from 12.9% to 0%. The results of test and simulation analysis conform well. The problem of untimely deviation correction was solved, which verified the effectiveness of the improved mechanism.

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Section: Establishment Of Finite Element Model Of the Deviation Corre...mentioning

confidence: 99%

Research on transient displacement response of the deviation correction mechanism of lithium-ion battery high-speed winding machine

Xia¹,

Lin²,

Yu³

et al. 2023

3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023)

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“…Parallel manipulators (PMs) offer better characteristics over serial manipulators in terms of overall rigidity, dynamic performance, payloads and accuracy (Xu et al , 2017). The closed configurations of most 6-DoF PMs have complicated forward kinematics, coupled motions for the end effector and limited workspace.…”

Section: Introductionmentioning

confidence: 99%

Comparative study of various machine learning algorithms and Denavit–Hartenberg approach for the inverse kinematic solutions in a 3-PPSS parallel manipulator

Thomas

Sanjeev

Sudheer

et al. 2020

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Purpose This paper aims to use different machine learning (ML) algorithms for the prediction of inverse kinematic solutions in parallel manipulators (PMs) to overcome the computational difficulties and approximations involved with the analytical methods. The results obtained from the ML algorithms and the Denavit–Hartenberg (DH) approach are compared with the experimental results to evaluate their performances. The study is performed on a novel 6-degree of freedom (DoF) PM that offers precise motions with a large workspace for the end effector. Design/methodology/approach The kinematic model for the proposed 3-PPSS PM is obtained using the modified DH approach and its inverse kinematic solutions are determined using the Levenberg–Marquardt algorithm. Various prediction algorithms such as the multiple linear regression, multi-variate polynomial regression, support vector, decision tree, random forest regression and multi-layer perceptron networks are applied to predict the inverse kinematic solutions for the manipulator. The data set required to train the network is generated experimentally by recording the poses of the end effector for different instantaneous positions of the slider using the concept of ArUco markers. Findings This paper fully demonstrates the possibility to use artificial intelligence for the prediction of inverse kinematic solutions especially for complex geometries. Originality/value As the analytical models derived from the geometrical method, Screw theory or numerical techniques involve approximations and needs more computational power, it is not advisable for real-time control of the manipulator. In addition, the data set obtained from the derived inverse kinematic equations to train the network may lead to inaccuracies in the predicted results. This error may generate significant deviations in the end-effector position from the desired position. The present work attempts to resolve this issue by proposing a camera-based approach that uses ArUco library and ML algorithms to create the data set experimentally and predict the inverse kinematic solutions accurately.

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“…Robot calibration can be divided into robot kinematic calibration and nonkinematic calibration [9][10][11]. e latter mainly includes the identification of structural robot deformation errors caused by the change of temperature [12], the link self-gravity of robots, and the change of external payload [13][14][15][16][17][18], as well as the calibration of dynamic parameters [19][20][21][22]. All the above calibration methods need the error model, which is based on the structural parameters of robots.…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Robot Calibration and Nonlinear Compensation Methodology Based on GA-DNN and an Extra Compliance Error Model

Chen

Zhang

Sun

2020

Mathematical Problems in Engineering

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This study addresses the problem of nonlinear error predictive compensation to achieve high positioning accuracy for advanced industrial applications. An improved calibration method based on the generalisation performance evaluation is proposed to enhance the stability and accuracy of robot calibration. With the development of technology, a deep neural network (DNN) optimised by a genetic algorithm (GA) is applied to predict the nonlinear error of the calibrated robot. To address the change of external payload, an extra compliance error model is established with a linear piecewise method. A global compensation method combining the GA-DNN nonlinear regression prediction model and the compliance error model is then proposed to achieve the robot’s high-precision positioning performance under any external payload. Experimental results obtained on a Staubli RX160L robot with a FARO laser tracker are introduced to demonstrate the effectiveness and benefits of our proposed methodology. The enhanced positioning accuracy can reach 0.22 mm with 98% probability (i.e., the maximum positioning error in all test data).

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Stiffness modeling and optimization of a 3-DOF parallel robot in a serial-parallel polishing machine

Cited by 35 publications

References 37 publications

Research on transient displacement response of the deviation correction mechanism of lithium-ion battery high-speed winding machine

Research on transient displacement response of the deviation correction mechanism of lithium-ion battery high-speed winding machine

Comparative study of various machine learning algorithms and Denavit–Hartenberg approach for the inverse kinematic solutions in a 3-PPSS parallel manipulator

Evolutionary Robot Calibration and Nonlinear Compensation Methodology Based on GA-DNN and an Extra Compliance Error Model

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