Sánchez-Gómez, Claudia
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Preferred name
Sánchez-Gómez, Claudia
Official Name
Sánchez Gómez, Claudia Nallely
Alternative Name
cnsanchez
Main Affiliation
ORCID
Scopus Author ID
57201851558
Researcher ID
DTU-3417-2022

Research Output
Now showing 1 - 10 of 30
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Publication

Complete Balancing of the Six-Bar Mechanism Using Fully Cartesian Coordinates and Multiobjective Differential Evolution Optimization

2022 , Orvañanos-Guerrero, María T. , Acevedo, Mario , Daniel U. Campos-Delgado , Sánchez-Gómez, Claudia , Amir Aminzadeh Ghavifekr , Paolo Visconti , Velázquez, Ramiro

The high-speed operation of unbalanced machines may cause vibrations that lead to noise, wear, and fatigue that will eventually limit their efficiency and operating life. To restrain such vibrations, a complete balancing must be performed. This paper presents the complete balancing optimization of a six-bar mechanism with the use of counterweights. A novel method based on fully Cartesian coordinates (FCC) is proposed to represent such a balanced mechanism. A multiobjective optimization problem was solved using the Differential Evolution (DE) algorithm to minimize the shaking force (ShF) and the shaking moment (ShM) and thus balance the system. The Pareto front is used to determine the best solutions according to three optimization criteria: only the ShF, only the ShM, and both the ShF and ShM. The dimensions of the counterweights are further fine-tuned with an analysis of their partial derivatives, volumes, and area–thickness relations. Numerical results show that the ShF and ShM can be reduced by 76.82% and 77.21%, respectively, when importance is given to either of them and by 45.69% and 46.81%, respectively, when equal importance is given to both. A comparison of these results with others previously reported in the literature shows that the use of FCC in conjunction with DE is a suitable methodology for the complete balancing of mechanisms.

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Publication

Gradient Descent-Based Optimization Method of a Four-Bar Mechanism Using Fully Cartesian Coordinates

2019 , Orvañanos-Guerrero, María T. , Sánchez-Gómez, Claudia , Mariano Rivera , Acevedo, Mario , Velázquez, Ramiro

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.

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Publication

Night club recommendation system based on decision trees

2021 , Sánchez-Gómez, Claudia , Jose-Carlos Delgado-Gomez , Pablo Ramirez-Espana , Luis Garcia-Zermeno , Samantha Licea , Domínguez-Soberanes, Julieta

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Landscape images distance using kullback leibler divergence

2018 , Sánchez-Gómez, Claudia , Mario Graff , Domínguez-Soberanes, Julieta , Gutiérrez, Sebastián

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Facial Emotion Recognition: A Comparison of Different Landmark-Based Classifiers

2018 , Álvarez-Pato, Víctor M. , Sánchez-Gómez, Claudia , Gutiérrez, Sebastián , Domínguez-Soberanes, Julieta , Velázquez, Ramiro

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Modeling of Amorphous-Carbon Cells for Molecular Dynamics Simulations

2019 , Sánchez-Gómez, Claudia , Domínguez-Soberanes, Julieta , ORTIZ-MEDINA, JOSUE

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Heidegger and the simile of the cave. The assumptions of its interpretation

2020 , Domínguez-Soberanes, Julieta , Sánchez-Gómez, Claudia , Orvañanos-Guerrero, María T.

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A forgotten and unforgettable story. Carranza, Constitution and Catholic Church in Mexico (1914-1919)

2022 , Velázquez, Ramiro , Acevedo, Mario , Sánchez-Gómez, Claudia , Orvañanos-Guerrero, María T.

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Recommendation System for a Delivery Food Application Based on Number of Orders

2023 , Sánchez-Gómez, Claudia , Domínguez-Soberanes, Julieta , Alejandra Arreola , Mario Graff

With the recent growth in food-delivery applications, creating new recommendation systems tailored to this platform is essential. State-of-the-art restaurant recommendation systems are based on users’ ratings or reviews, with data that are obtained from questionnaires or online platforms such as TripAdvisor, Zomato, Foursquare, or Yield. However, not all users give ratings or reviews after their purchase. This document proposes a recommendation system whose input is the number of orders stored by a real food-delivery application. These data are always available for all food-delivery applications and are stored all the time. Our proposal is based on the nearest-neighbor technique that calculates the client’s preferred restaurants and analyzes other clients with similar buying patterns. In addition, we propose a performance metric that can be used for this specific recommendation system that is based on real restaurant sales. We use a real dataset (available online) to validate our proposal. Based on our experiments, the recommendation system successfully gives only an average of 7.7 options from 187 that are available. We compared our proposal with other state-of-the-art recommendation techniques and obtained a better performance. Our results indicate that it is possible to generate recommendations based on the number of orders, making the use of a restaurant-recommendation system feasible in a real food-delivery application.

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Robust multiband image segmentation method based on user clues

2017 , Sánchez-Gómez, Claudia , Mariano Rivera , Velázquez, Ramiro

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