Optimum Synthesis of Four-Bar Mechanism by Using Relative Angle Method: A Comparative Performance Study

Valencia-Segura, Luis Ernesto; Villarreal-Cervantes, Miguel Gabriel; Corona-Ramirez, Leonel German; Cuenca-Jiménez, Francisco; Castro-Medina, Roberto

doi:10.1109/access.2021.3115444

Cited by 12 publications

(18 citation statements)

References 32 publications

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“…After determining the effectiveness of the SIDE concerning the other DE variants studied in this work, the results were contrasted with those obtained by algorithms in recent specialized literature for the dimensional synthesis of four-bar Grashof-type mechanisms. The works in [26,35] were selected for this purpose. In [35], the dimensional synthesis of the four-bar mechanism was tackled with nine advanced optimization algorithms for six case studies, including those from the benchmark in [40].…”

Section: Comparative Results Of Side With the Most Promising De Variantsmentioning

confidence: 99%

“…In [35], the dimensional synthesis of the four-bar mechanism was tackled with nine advanced optimization algorithms for six case studies, including those from the benchmark in [40]. On the other hand, the work in [26] proposed the dimensional synthesis of four-bar mechanisms through a parameterization based on a motion analysis with relative angles. This parameterization of the synthesis problem was solved through DE for five case studies, three of which corresponded to those of the benchmark in [40].…”

Section: Comparative Results Of Side With the Most Promising De Variantsmentioning

confidence: 99%

“…The best results obtained by the SIDE and by the algorithms used in [26,35] are presented in for each case study. The columns of these tables show the values of the design variables calculated with each algorithm, while the value of the objective function J( p) achieved with them is noted at the bottom.…”

Section: Ref Sidementioning

confidence: 99%

“…The first three methods are helpful for synthesizing four-bar mechanisms when the trajectories (paths) are relatively simple. As trajectories become more complicated, the optimization method turns out to be more effective, so its use is now widespread [22][23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

“…The four-bar mechanism is one of the most widely used in various applications and complex machines such as sewing machines, round balers, suspension systems of automobiles, pumpjacks, prosthetic knees, and others, because this mechanism can trace complex trajectories by appropriately setting link lengths without the need to use complex mechanisms, even though the latter can provide significant flexibility in the synthesis [34]. Thus, nowadays, researchers are continually coming up with new approaches to state and resolve the four-bar mechanism's synthesis problem [26,35] to improve the quality of design objectives. Thus, this work developed a comparative study of the most-used variants of DE in search of the solution to the most common conceptualizations of the dimensional synthesis problem of four-bar Grashof-type mechanisms.…”

Section: Introductionmentioning

confidence: 99%

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Study of Differential Evolution Variants in the Dimensional Synthesis of Four-Bar Grashof-Type Mechanisms

Rodríguez-Molina,

Villarreal-Cervantes,

Rueda-Gutiérrez

et al. 2023

Applied Sciences

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Mechanisms have allowed for the automation of complex, repetitive, demanding, or dangerous tasks for humans. Among the different mechanisms, those with a closed kinematic chain are more precise and robust compared to open chain ones, which makes them suitable for many applications. One of the most widely used closed-chain alternatives is the four-bar Grashof-type mechanism, as it can generate highly nonlinear closed trajectories with a single degree of freedom. However, the dimensional synthesis of these mechanisms to generate specific trajectories is a complex task. Fortunately, computational methods known as metaheuristics can solve such problems effectively. Differential Evolution (DE) is a metaheuristic commonly used to tackle the dimensional synthesis problem. This paper presents a comparative study of the most commonly used variants of DE in solving the dimensional synthesis problem of four-bar Grashof-type mechanisms. The purpose of the study is to provide guidelines to choose the best DE alternative for solving problems of this type, as well as to support the development of DE-based algorithms that can solve more specific cases effectively. After analysis, the rand/1/exp variant was found to be the most effective in solving the dimensional synthesis problem, which was followed by best/1/bin. Based on these results, a Simple and Improved DE (SIDE) variant based on these two was proposed. The competitive performance of the SIDE with respect to the studied DE variants and in contrast to the results of algorithms used in the recent specialized literature for mechanism synthesis illustrates the usefulness of the study.

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Section: Comparative Results Of Side With the Most Promising De Variantsmentioning

confidence: 99%

Section: Comparative Results Of Side With the Most Promising De Variantsmentioning

confidence: 99%

Section: Ref Sidementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Study of Differential Evolution Variants in the Dimensional Synthesis of Four-Bar Grashof-Type Mechanisms

Rodríguez-Molina,

Villarreal-Cervantes,

Rueda-Gutiérrez

et al. 2023

Applied Sciences

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Bi-objective pareto optimization of centric crank-rocker mechanisms

Al-Dwairi

2024

Cogent Engineering

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Research on four-bar linkage trajectory synthesis using extreme gradient boosting and genetic algorithm

Wang,

Chen,

Wang

et al. 2024

Journal of Computational Design and Engineering

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The current study on the synthesis problems of four-bar mechanism trajectories primarily relies on establishing a numerical atlas based on trajectory characteristics and employing neural networks to synthesize mechanism parameters. However, this approach has several shortcomings, including a vast database, inefficient retrieval, and challenges in maintaining accuracy. This paper presents a method for synthesizing a trajectory-generation mechanism that combines the extreme gradient boosting (XGBoost) algorithm with a genetic algorithm (GA). The purpose is to synthesize, based on a particular trajectory, the dimensions and installation position parameters of a four-bar mechanism. The paper classifies the trajectories according to their shape features and geometric center placements, thereby improving the accuracy of the XGBoost model for synthesizing mechanisms. The XGBoost algorithm is employed to synthesize the basic dimensional parameters for the mechanism, with the relative slopes of trajectories as input features. The synthesized basic dimensional parameters are turned into parameters for the actual mechanism by researching the scaling, translation, and rotation relationships between mechanisms and the trajectories they generate. The accuracy of the generated trajectories from the synthesized mechanism can be improved by applying GA to optimize the mechanism parameters. Five comparative examples are provided in this research for the different scenarios of given trajectory curves and trajectory points. The effectiveness and accuracy of the proposed approach in this study are validated in comparison to existing research methods by comparing errors between the generated trajectories and the given trajectories.

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Optimum Synthesis of Four-Bar Mechanism by Using Relative Angle Method: A Comparative Performance Study

Cited by 12 publications

References 32 publications

Study of Differential Evolution Variants in the Dimensional Synthesis of Four-Bar Grashof-Type Mechanisms

Study of Differential Evolution Variants in the Dimensional Synthesis of Four-Bar Grashof-Type Mechanisms

Bi-objective pareto optimization of centric crank-rocker mechanisms

Research on four-bar linkage trajectory synthesis using extreme gradient boosting and genetic algorithm

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