Orvañanos-Guerrero, María T.

Preferred name

Official Name

Orvañanos Guerrero, María Teresa

Alternative Name

torvananos

Main Affiliation

ORCID

0000-0002-1060-0443

Scopus Author ID

57208530684

Researcher ID

AAA-4499-2020

Now showing 1 - 10 of 17

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Optimización del balanceo de un mecanismo plano mediante redistribución de masas
(2022)
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Juan Cisneros-Barba
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Miguel Carrasco
9 2
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Design and Characterization of a Miniature Bio-Inspired Mobile Robot
(2021)
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Claudia L. Garzon-Castro
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Amir A. Ghavifekr
This paper presents the design, implementation, and characterization of a miniature crab-like walking robot. The first prototype developed is a four-legged servomotor actuated machine that exhibits compact dimensions, low mass, and is capable of overcoming obstacles and moving on irregular terrain and confined spaces. Its bio-inspired design ensures the compliance of its locomotion mechanism even in the presence of external disturbances. The mechanical design, the implementation of the prototype, and its electronic control approach are first discussed. Next, a kinematic analysis characterizing its motion is presented. The aim of this device is to serve as an educational supporting platform for understanding robot kinematics and legged locomotion.
Scopus© Citations 6 14 1
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Análisis y optimización de mecanismos para el balanceo dinámico utilizando coordenadas naturales
(2022-01)
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RAMIRO VELÁZQUEZ GUERRERO;40848
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Acevedo, Mario
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Velázquez Guerrero, Ramiro
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Campus Aguascalientes
Esta tesis explora la optimización del balanceo dinámico en diferentes tipos de mecanismos en el plano para lograr la reducción máxima de las reacciones correspondientes a la Fuerza de Sacudimiento y al Momento de Sacudimiento a través de la redistribución de masas. Las expresiones que definen las reacciones dinámicas en la base del mecanismo se obtienen de manera analítica, gracias al modelado realizado en coordenadas completamente cartesianas. Esto permite ensamblar una matriz de masas constante para todo el mecanismo, en donde además pueden identificarse fácilmente las condiciones de balanceo dinámico. La optimización se lleva a cabo mediante contrapesos calculados utilizando los algoritmos de Descenso de Gradiente y Evolución Diferencial, y se analizan utilizando Frentes de Pareto. En la mayoría de los casos se realizan análisis de sensibilidad, empleando también Frentes de Pareto, que permiten conocer la importancia que cada contrapeso tiene para el balanceo general. Además, se presenta una propuesta para el análisis de las restricciones de la optimización, empleando diagramas de caja. Usando las técnicas propuestas es posible lograr mejoras de hasta el 99.70% en la Fuerza de Sacudimiento y de hasta un 97.56% en el Momento de Sacudimiento, o incluso mayores al 50% en ambos casos cuando se utiliza únicamente un contrapeso.
17 290
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Analysis of Meat Color Change using Computer Vision
(2020)
Gustavo Meza
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Scopus© Citations 1 16 1
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Shaking Moment Balancing of a Four-Bar Mechanism Using Actuation Redundancy
(2019)
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Scopus© Citations 2 31 2
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Optimum Balancing of the Four-Bar Linkage Using Fully Cartesian Coordinates
(2019)
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Haro-Sandoval, Eduardo
Scopus© Citations 10 19 2
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Efficient Balancing Optimization of a Simplified Slider-Crank Mechanism
(2020)
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Nicola Ivan Giannoccaro
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Paolo Visconti
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Scopus© Citations 3 10 2
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A forgotten and unforgettable story. Carranza, Constitution and Catholic Church in Mexico (1914-1919)
(2022)
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12 1
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Fuzzy Rule-Based Combination Model for the Fire Pixel Segmentation
(Institute of Electrical and Electronics Engineers (IEEE), 2025)
Lopez-Alanis, Alberto
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de-la-Torre-Gutierrez, Hector
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Hernández-Aguirre, Arturo
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Color-feature-based wildfire pixel segmentation has become a challenging task extensively addressed in various research studies. Rule-based models aim to identify fire pixels in a binary manner by determining whether the pixel intensity exceeds a specified threshold value. The authors determine the thresholds by analyzing diverse collections of images that contain wildfires. This has resulted in a lack of consensus on the thresholds determined by various researchers, even when the same color space is used during the examination process. Additionally, determining fire pixels in a binary manner complicates the handling of uncertainty and vagueness in color information. This research aims to enhance fire-pixel segmentation by integrating color-based rule models with a fuzzy set approach, which effectively addresses uncertainty and vagueness. The proposed approach automatically learns the optimal set of fuzzy operators and rules for fire detection to construct a combined model. To address the limitations of combining binary class labels, this approach modifies the rule form proposed by various authors to obtain a fuzzy set of data, such as a grayscale fire map, instead of a crisp set of data, such as a binary fire map. In addition, our proposal uses a genetic algorithm approach to construct the best combination model. The final binary form of the fire map is calculated using the widely used Otsu method. The presented method is evaluated qualitatively and quantitatively in a well-accepted dataset designed for wildfire pixel segmentation tasks. The model obtained outperforms state-of-the-art rules and traditional strategies for combining binary labels in the F-measure and IoU metrics. © 2013 IEEE.
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Gradient Descent-Based Optimization Method of a Four-Bar Mechanism Using Fully Cartesian Coordinates
(2019)
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Mariano Rivera
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<jats:p>Machine vibrations often occur due to dynamic unbalance inducing wear, fatigue, and noise that limit the potential of many machines. Dynamic balancing is a main concern in mechanism and machine theory as it allows designers to limit the transmission of vibrations to the frames and base of machines. This work introduces a novel method for representing a four-bar mechanism with the use of Fully Cartesian coordinates and a simple definition of the shaking force (ShF) and the shaking moment (ShM) equations. A simplified version of Projected Gradient Descent is used to minimize the ShF and ShM functions with the aim of balancing the system. The multi-objective optimization problem was solved using a linear combination of the objectives. A comprehensive analysis of the partial derivatives, volumes, and relations between area and thickness of the counterweights is used to define whether the allowed optimization boundaries should be changed in case the mechanical conditions of the mechanism permit it. A comparison between Pareto fronts is used to determine the impact that each counterweight has on the mechanism’s balancing. In this way, it is possible to determine which counterweights can be eliminated according to the importance of the static balance (ShF), dynamic balance (ShM), or both. The results of this methodology when using three counterweights reduces the ShF and ShM by 99.70% and 28.69%, respectively when importance is given to the static balancing and by 83.99% and 8.47%, respectively, when importance is focused on dynamic balancing. Even when further reducing the number of counterweights, the ShF and ShM can be decreased satisfactorily.</jats:p>
Scopus© Citations 11 14 2

Orvañanos-Guerrero, María T.

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