Backlash analysis of RV reducer based on Error Factor Sensitivity and Monte-Carlo Simulation

Sun, Yao; Zhao, Xingwei; Jiang, Fengrui; Li, Zhao; Liu, D.; Yu, G. B.

doi:10.14257/ijhit.2014.7.2.25

Cited by 14 publications

(12 citation statements)

References 2 publications

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“…erefore, it is determined that there are 50 nodes in the hidden layer, represented by R i . e weight from T i to R i is uik, using the relationship between the additional torque and the torque transmitted by the shaft shown in equation (10). e input signal is transformed by the function shown in equation (10) and sent to the hidden layer.…”

Section: Error Compensation Methodmentioning

confidence: 99%

“…e weight from T i to R i is uik, using the relationship between the additional torque and the torque transmitted by the shaft shown in equation (10). e input signal is transformed by the function shown in equation (10) and sent to the hidden layer. e hidden layer unit is transformed by the radial basis function and sent to the output layer.…”

Section: Error Compensation Methodmentioning

confidence: 99%

“…e performance parameters of the reducer generally include the no-load friction torque, torsional stiffness, and transmission efficiency [3,7,8]. Many scholars have extensively studied the optimization of the internal parts [9], overall structure [10], and dynamic performance of the reducer [11,12]. However, these studies are limited by measurement means and equipment, which severely hinders the improvements to the reducer performance.…”

Section: Introductionmentioning

confidence: 99%

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Design and Calibration of Torque Measurement System of Comprehensive Performance Test Instrument of Industrial Robot Reducer

Qiu

et al. 2022

Computational Intelligence and Neuroscience

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The measurement of input and output torque of a precision reducer, the core component of an industrial robot, plays a vital role in evaluating the robot's performance. The TMSIS and TMSOS of a vertical cylindrical high-precision reducer detector were designed and investigated in this study to realize the accurate measurement of input and output torque of the reducer. Because a transmission chain connects the torque transducer and the reducer, the characteristics of the inevitable additional torque are analyzed in detail. A torque calibration device is developed to realize the calibration of the torque measurement system. The readings of the torque calibration device are compared with the data of the instrument’s torque measurement system to realize the instrument's torque calibration. The improved particle swarm optimization and Levenberg–Marquardt algorithm-based radial basis function neural network is used to compensate for the error of the torque measurement system. The parameters of the RBF neural network are settled according to the characteristics of the additional torque and the torque calibration results. The experimental results show that the torque measurement accuracy of the torque measurement system can reach 0.1% FS after torque calibration and error compensation.

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Section: Error Compensation Methodmentioning

confidence: 99%

Section: Error Compensation Methodmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Design and Calibration of Torque Measurement System of Comprehensive Performance Test Instrument of Industrial Robot Reducer

Qiu

et al. 2022

Computational Intelligence and Neuroscience

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“…The uneven frictional force caused by deformation of the components and the misalignment error can lead to torque fluctuation. The above troubles inevitably disturb the measurements of torque [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Torque Measurement of High‐Precision Reducer for Industrial Robot

Zhang

2021

Journal of Sensors

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Torque testing is crucial to improve the quality of high-precision reducers—the core component of industrial robots. Herein, a torque-measurement system for a novel vertical measuring instrument is designed. The distance from the torque transducers to the robot reducer is minimized to ensure the shortest measurement chain. The symmetrical system structure improves the overall rigidity, and error compensation can be performed easily. The characteristics of the torque measurement errors due to shaft bending and torsional deformations were also analyzed. A torque calibrator comprising two high-precision torque output systems was used to calibrate torque transducers in the measurement system. Reasonable and practical compensation models based on a backpropagation neural network were developed to accurately obtain the input and output torques of the reducer. As the torque-measurement precision of the reducer detector reached 0.1% over the entire torque range, the instrument can be used for accuracy measurement of the input and output torques of the robot reducer.

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“…In the paper, the sensitivities and weights of error factors need to be Technical Editor: Zilda de Castro Silveira, Ph.D. prescribed in advance. Sun et al [23] studied the backlash of an RV reducer based on error factor sensitivity. In the paper, a backlash model was proposed and various error factors were considered.…”

Section: Introductionmentioning

confidence: 99%

Kinematic error analysis of the rotor vector gear reducer with machining tolerances

Shih

Lee

2020

J Braz. Soc. Mech. Sci. Eng.

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The rotor vector (RV) gear reducer is a mechanism used for motion and torque transmission. With characteristics similar to a traditional cycloidal gear drive, it has been popularly applied in precision machinery because of its high-speed reduction ratio, large torque capacity, and high efficiency. In this work, we aim to analyze the kinematic error (transmission error) of the RV reducer with manufacturing and/or assembly tolerances. Formulae for the kinematic error are established by using the theory of gearing as well as tooth contact analysis. Subsequently, sensitivities of the kinematic error with respect to various design parameters are investigated. Lastly, a process to simulate the distribution of maximum kinematic errors of the gear reducer with various tolerance grades of the parts is developed via Monte Carlo method. It is shown that through selected tolerance control on the machine parts, the accuracy of the gear drive can be retained. The results of this work can be useful for controlling the manufacturing precision on the machine parts and assessing the overall accuracy of the mechanism in the design phase.

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Backlash analysis of RV reducer based on Error Factor Sensitivity and Monte-Carlo Simulation

Cited by 14 publications

References 2 publications

Design and Calibration of Torque Measurement System of Comprehensive Performance Test Instrument of Industrial Robot Reducer

Design and Calibration of Torque Measurement System of Comprehensive Performance Test Instrument of Industrial Robot Reducer

Torque Measurement of High‐Precision Reducer for Industrial Robot

Kinematic error analysis of the rotor vector gear reducer with machining tolerances

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