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Modal Complexity Factors as indexes for modal parameter identification in operational modal analysis of coupled dynamic systems
(Elsevier, 2025-03-31) Ibarrola Chamizo, Javier; Agirre Olabide, Iker; Merino Olagüe, Mikel; Aginaga García, Jokin; Ingeniería; Ingeniaritza; Institute of Smart Cities - ISC; Gobierno de Navarra / Nafarroako Gobernua
Vibration analysis seeks to extract the modal parameters of a mechanical system by means of experimental measurements. Natural frequencies, damping ratios and mode shapes are identified from the measurements data from experimental or operational modal analysis. Modal shapes can show real or complex values. The degree of complexity of a modal shape can be measured by the Modal Complexity Factors (MCF). Among others, modal complexity can be due to non-uniformly distributed damping. In complex mechanical systems like a robot, complex modes are expected due to its active and non distributed damping. In turn, in a metallic workpiece real modes are expected. In the robotic machining of thin workpieces, both the robot and the workpiece constitute a coupled dynamic system, operating within the same frequency range. This work proposes the use of MCFs as indexes to determine if each mode corresponds to the workpiece or the robot. Experimental results of an operational modal analysis show a lower mode complexity for the workpiece modes and a higher complexity for the robot frequencies. MCFs show a good performance in separating modes of such coupled systems due to the different damping nature of the robot and the workpiece.
Open Access
Dataset for the identification of a ultra-low frequency multidirectional energy harvester for wind turbines
(Elsevier, 2024-11-20) Bacaicoa Díaz, Julen; Hualde Otamendi, Mikel; Merino Olagüe, Mikel; Plaza Puértolas, Aitor; Iriarte Goñi, Xabier; Castellano Aldave, Jesús Carlos; Carlosena García, Alfonso; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza; Ingeniería; Ingeniaritza; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
This paper presents a publicly available dataset designed to support the identification (characterization) and performance optimization of an ultra-low-frequency multidirectional vibration energy harvester. The dataset includes detailed measurements from experiments performed to fully characterize its dynamic behaviour. The experimental data encompasses both input (acceleration)-output (energy) relationships, as well as internal system dynamics, measured using a synchronized image processing and signal acquisition system. In addition to the raw input-output data, the dataset also provides post-processed information, such as the angular positions of the moving masses, their velocities and accelerations, derived from recorded high-speed videos at 240 Hz. The dataset also includes the measured power output generated in the coils. This dataset is intended to enable further research on vibration energy harvesters by providing experimental data for identification, model validation, and performance optimization, particularly in the context of energy harvesting in low-frequency and multidirectional environments, such as those encountered in wind turbines.
Open Access
Modelado multiplataforma para el control de un sistema articulado
(UNED, 2023) Ibarrola Chamizo, Javier; Merino Olagüe, Mikel; Iriarte Goñi, Xabier; Hualde Otamendi, Mikel; Ingeniería; Ingeniaritza; Institute of Smart Cities - ISC
En el presente artículo se ha trabajado con las herramientas de simulación de sistemas mecánicos Gazebo y Simulink, realizando una interconexión entre ambos con el fin de desglosar la parte dinámica y cinemática de la parte de control, obtención y tratamiento de datos. La vía de enlace entre ambos programas se realiza mediante otro software de comunicación, ROS. Con todo ello, se ha conseguido la cosimulación de un mecanismo articulado en la cual, Simulink comanda trayectorias a Gazebo a través de pares en articulaciones, Gazebo envía los valores de posición articular de la simulación a Simulink, y mediante el control multiarticular de pares realimentados diseñado en este último programa, se minimiza el error entre la trayectoria simulada y la ideal. La obtención de los parámetros del modelo dinámico requeridos en el control se ha realizado mediante una librería de Matlab (Lib_3D_MEC_Matlab) de análisis de sistemas multicuerpo desarrollada por la UPNA.
Open Access
AI training for application to industrial robotics: trajectory generation for neural network tuning
(Springer, 2023) Merino Olagüe, Mikel; Ibarrola Chamizo, Javier; Aginaga García, Jokin; Hualde Otamendi, Mikel; Ingeniería; Ingeniaritza; Institute of Smart Cities - ISC
In the present work robot trajectories are generated and kinematically simulated. Different data (joint coordinates, end effector position and orientation, images, etc.) are obtained in order to train a neural network suited for applications in robotics. The neural network has the goal of automatically generating trajectories based on a set of images and coordinates. For this purpose, trajectories are designed in two separate sections which are conveniently connected using Bezier curves, ensuring continuity up to accelerations. In addition, among the possible trajectories that can be carried out due to the different configurations of the robot, the most suitable ones have been selected avoiding collisions and singularities. The designed algorithm can be used in multiple applications by adapting its different parameters.

Merino Olagüe, Mikel

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