| Autor: |
Salvador Martínez-Cruz, Juan P. Amézquita-Sánchez, Gerardo I. Pérez-Soto, Jesús R. Rivera-Guillén, Luis A. Morales-Hernández, Karla A. Camarillo-Gómez |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Sensors, Vol 21, Iss 4, p 1209 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
1424-8220 |
| DOI: |
10.3390/s21041209 |
| Popis: |
In this paper, the natural frequencies (NFs) identification by finite element method (FEM) is applied to a two degrees-of-freedom (2-DOF) planar robot, and its validation through a novel experimental methodology, the Multiple Signal Classification (MUSIC) algorithm, is presented. The experimental platforms are two different 2-DOF planar robots with different materials for the links and different types of actuators. The FEM is carried out using ANSYS™ software for the experiments, with vibration signal analysis by MUSIC algorithm. The advantages of the MUSIC algorithm against the commonly used fast Fourier transform (FFT) method are also presented for a synthetic signal contaminated by three different noise levels. The analytical and experimental results show that the proposed methodology identifies the NFs of a high-resolution robot even when they are very closed and when the signal is embedded in high-level noise. Furthermore, the results show that the proposed methodology can obtain a high-frequency resolution with a short sample data set. Identifying the NFs of robots is useful for avoiding such frequencies in the path planning and in the selection of controller gains that establish the bandwidth. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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