Bibliographic Details
| Title: |
Spectral Identification of Inertial Parameters in Forced Sinusoidal Regimes. |
| Authors: |
Robert, Clément1,2 clement.robert@lirmm.fr, Krut, Sébastien1 sebastien.krut@lirmm.fr, Company, Olivier1 company@lirmm.fr, Vissiere, Alain3 alain.vissiere@lecnam.net, Noire, Pierre2 pierre.noire@symetrie.fr, Pierrot, François1 francois.pierrot@lirmm.fr |
| Source: |
Journal of Dynamic Systems, Measurement, & Control. Jul2026, Vol. 148 Issue 4, p1-12. 12p. |
| Subjects: |
Fourier transforms, Parallel robots, Parameter estimation, Torquemeters, Frequency-domain analysis, Rigid body mechanics, Inertial mass |
| Abstract: |
This paper presents an approach for identifying all the inertial parameters of a solid (mass, position of the center of gravity, and inertia matrix) without repositioning the solid. The identification is based on the use of a hexapod parallel robot capable of six degree-of-freedom (DOF) motions and a 6-component force/torque sensor. The solid to be characterized is placed on the sensor, which is attached to the robot. The robot is used to impose different sinusoidal excitation trajectories in succession. The reaction forces are recorded at the same time, and the inertial parameters are identified by solving the Newton-Euler equations in the frequency domain using the Fourier transform. This solution in the frequency domain allows for precise computation with the following advantages: (i) maximum decoupling of the equations for optimal resolution, individually adapted to each parameter; (ii) simplicity of the experimental setup and the resolution method. Only three elements are required (the solid to be evaluated, the force/torque sensor, and the robot). Data processing is not overly complex and does not require overly restrictive synchronization of the clocks of the different systems; (iii) fine adjustment of the force/torque sensor (offset calibration) is not necessary. [ABSTRACT FROM AUTHOR] |
|
Copyright of Journal of Dynamic Systems, Measurement, & Control is the property of American Society of Mechanical Engineers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Engineering Source |