Statistical analysis of the influence of tooth geometry in the performance of a harmonic drive
The objective of this research is to determine the influence of gear tooth geometrical variations in the performance of a double wave harmonic drive through statistical analysis. This work incorporates state of the art analytical and numerical models to evaluate kinematic error, load capacity, bending fatigue strength, and pitting. The geometric variables considered in this study include gear modulus, pressure angle, and tooth correction factor. The statistical analysis follows a three-level full-factorial design of experiments. Nonlinear dynamic simulation is accompanied by finite element analysis to estimate contact and bending stresses. Largest bending fatigue strength is also determined. Results demonstrate that gear modulus is the geometric parameter with prevalent influence on the kinematic error, and pitting life is rather high for all geometric variables considered.
A new robotic drive joint friction compensation mechanism using neural networks
The knowledge of realistic dynamic models to robotic actuators would be of great aid in the synthesis of control laws to robot manipulators, mainly in cases of great precision robotic or even for manipulators with flexible links. In this paper we present a training scheme and propose a structure of neural network (NN) to learn the friction torque of a geared motor drive joint robotic actuator. To train the NN was used experimental data obtained by an harmonic-drive actuator, equipped with an encoder to measure the rotor angular position. It was considered the motor torque and the rotor angular velocity as NN input, while the friction torque was the only output, which was used in the proposition of a non-linear friction compensation mechanism. The experimental results attested the efficiency of the NN friction estimation and compensation with the proposed mechanism.
A comparison of Newton-Raphson methods and incremental procedures for geometrically nonlinear analysis
Abstract A unique relationship is found herein among four very important and related solution methods for geometrically nonlinear analysis. This relationship allows one to better understand the discrepancies between results obtained by these methods. Suggestions can then be made with respect to the most appropriate method by considering the required accuracy of the solution in conjunction with the costs of computation.