Hybrid Optimization Based Mathematical Procedure for Dimensional Synthesis of Slider-Crank Linkage (original) (raw)
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Engineering Optimization, 2018
This work deals with a multi-body system synthesis. A flexible slider crank mechanism has been investigated as an illustrative application. The main interest is focused on the mechanism design variables' identification based on its dynamic responses. Three responses have been involved such as the slider velocity, the slider acceleration and the mid-point transversal deflection of the flexible connecting rod. Each of these responses has been embroiled separately in a mono-objective optimization. Subsequently, the multi-objective optimization subsuming these responses has been established. Two different optimization methods have been studied namely the genetic algorithm (GA) and the particle swarm optimization (PSO) technique. It has been proved that the multi-objective optimization presents more accurate results beside the mono-objective optimization. Compared to the GA, the PSO is more powerful and is able to identify the mechanism design variable with better accuracy, in spite of the affordable computational time allowed with the GA optimization.
Artificial Intelligence Review, 2019
This work bespeaks an insight into a real imperfect multibody systems synthesis, wherein the flexible behaviour of its components is considered. Based on the end-effector mechanism velocity, acceleration and defined transversal deflection for a flexible component, the mechanism optimal design variables have been investigated. Subsequently, the three aforementioned responses have been involved simultaneously for a combined optimization process. To this end, an Assistance Tool Design, subsuming several meta-heuristic optimization techniques such as Genetic Algorithm (GA), Imperialist Competitive Algorithm (ICA), Artificial Bee Colony (ABC), Ant Colony (AC), Differential Evolution (DE) and Simulating Annealing (SA) techniques, has been developed under MATLAB software. The Assistance Tool Design enables designers to carry out the synthesis of mechanisms by means of one or many optimization techniques mentioned above. It has been proven that AC and DE outperform the other optimization techniques. Nevertheless, awkwardness has been bearded for the mechanism synthesis using only a single response, mainly the flexible connecting rod mid-point transversal deflection. The combined synthesis subsuming simultaneously the three responses discussed above settles a perfect trade-off for all the optimization techniques.
Optimal Kinematic Synthesis of Planar Mechanism, Part I: Offset Crank-Slider Mechanism
2015
Optimal synthesis of mechanisms is a successful approach for mechanism design to satisfy all the desired characteristics of the designed mechanism. The crank - slider mechanism has wide industrial applications and providing an offset feature provides a design with a stroke greater than its crank length and a time ratio greater than one. The optimal design problem in this case is a constrained multi-dimensional problem. Powell optimization technique is used to minimize a special objective function combining the mechanism stroke and time ratio. 2 functional constraint functions are used for the minimum and maximum transmission angle of the mechanism. The optimal results are fitted in a proper nonlinear model relating the normalized mechanism dimensions to the normalized stroke and time ratio. A comparison is conducted between the optimal design and the non-optimal one illustrating the advantages of the optimal approach.
Optimal dynamic design of a planar slider-crank mechanism with a joint clearance
Mechanism and Machine Theory, 2015
In general, in dynamic analysis of mechanisms, joints are assumed to be ideal without clearance. However, in reality, clearances in the joints are inevitable due to tolerances, and defects arising from design and manufacturing. When a joint clearance is introduced, the mechanism gains two uncontrollable degrees of freedom. Therefore, poor dynamic performance, reduction in components life and generation of undesirable vibrations result in the impacts of mating parts in the clearance joint. In this paper, an optimization method is proposed to alleviate the undesirable effects of joint clearance. The main consideration here is to optimize the mass distribution of the links of a mechanism to reduce or eliminate the impact forces in the clearance joint. An algorithm based on PSO solves this highly nonlinear optimization problem for a slider-crank mechanism with a revolute clearance joint between the slider and the connecting rod. Finally, an example is included to demonstrate the efficiency of the algorithm.
Design FlowChart of Slider-Crank Mechanisms and Applications
2009
This paper deals with the formulation of a suitable algorithm for the kinematic analysis of slidercrank mechanisms for automatic machinery, in terms of shape and characteristics of the coupler curves with the aid of the cubic of stationary curvature and the inflection circle. Moreover, a practical method for the kinematic synthesis of a slider-crank mechanism as path generator, is also proposed for the generation of a symmetrical egg shape path with an approximate straight line. In particular, starting from the knowledge of the shape and the overall sizes of the required coupler curve of the slider-crank mechanism, lengths of the coupler-link and crank-link can be obtained from the proposed practical method and design flow-chart.
Optimal Synthesis of Crank Rocker Mechanism for Point to Point Path Generation
2012
The Present Work Introduces The Concept Of Orientation Structure Error Of The Fixed Link And Present A New Optimal Synthesis Method Of Crank Rocker Linkages For Path Generation. The Orientation Structure Error Of The Fixed Link Effectively Reflects The Overall Difference Between The Desired And Generated Path. Avoid By Making Point By Point Comparisons Between The Two Paths And Requires No Prescription Of Timing. In The Kinematic Synthesis Of Four Bar Path Generating Linkages, It Is Required To Determine The Linkage Dimensions' So That A Point On The Coupler Link Traces Out The Desired Curve. There Are Two Types Of Task For Path Generation. One Of Them Specified Only Small Number Of Points On The Path, And The Trajectory Between Any Two Specified Point Is Not Prescribed. The Concept Of Orientation Structure Error Of The Fixed Link Is Introduced. A Simple And Effective Optimal Synthesis Method Of Crank -Rocker Path Generating Linkages Is Presented.
Optimization of transmission angle for slider-crank mechanism with joint clearances
Structural and Multidisciplinary Optimization, 2009
In this study, kinematic analysis of a planar slider-crank mechanism having revolute joints with clearances was presented. Joint clearance was modelled as a massless virtual link, and Multi-Layered Neural Network (MLNN) structure was used for approximating the motion of this link with respect to the position of input link. Training and testing data sets for the neural network were obtained from mechanism simulation using the ADAMS software. A genetic algorithm was also used to optimize the design parameters for minimizing the deviations due to clearances. When two joint clearances at crank-pin and piston-pin centers were considered, the effects of these clearances on the kinematic characteristics and transmission quality of the mechanism were investigated using continuous contact model between the journal and bearing at a joint.
Applied Mathematical Modelling, 2010
In this paper, Hamilton's principle, Lagrange multiplier, geometric constraints, partitioning method and Baumgarte stabilization method (BSM) are employed to derive the dynamic equations of a spatial slider-crank mechanism that is driven by a servomotor. The formulation considers the effects of links masses, external forces and motor electric inputs. Comparing dynamic responses between the experimental results and numerical simulations, dynamic modeling gives a wonderful interpretation for the spatial slider-crank mechanism. In this paper, a new identification method based on real-coded genetic algorithm (RGA) is presented to identify the parameters of a spatial slider-crank mechanism. The method promotes the calculation efficiency very much, and is calculated by real-code without the operations of encoding and decoding. The results of numerical simulations and experimental results prove that the identification method is feasible. The contributions of this paper are that the comparison of mathematical modeling and identification between numerical simulations and experimental results are all realized.
International Journal of Scientific Research in Science, Engineering and Technology, 2021
The paper focuses on synthesis of slider crank mechanism consisting of a single gear as a part of input and output of the mechanism. Complex number method is used as one of the synthesis criteria. This is a planar four link gear slider mechanism having one degree of freedom which is considered for synthesis using variable topology method for the task of motion generation. The mechanism consists of three revolute and one slider joints. Synthesized mechanism exhibits the features of variable topology mechanism in different modes of operation.
A combined genetic algorithm–fuzzy logic method (GA–FL) in mechanisms synthesis
Mechanism and Machine Theory, 2004
This work presents a combined genetic algorithm-fuzzy logic method to solve the problem of path generation in mechanism synthesis. The proposed method is made of a classical genetic algorithm coupled with a fuzzy logic controller (GA-FL). This controller monitors the variation of the design variables during the first run of the genetic algorithm and modifies the initial bounding intervals to restart a second round of the genetic algorithm. Compared to previous works on the same problem, our method proved to be more efficient in finding the optimal mechanism. Mechanism and Machine Theory techniques very demanding in computation time and in some cases they may even fail to converge. Three types of problems are found in mechanism synthesis: function generation, trajectory generation and body guidance . In this work, we will present the trajectory generation problem, an extension to the problem of body guidance is currently investigated. Lately, new methods based on artificial intelligence or probabilistic approach emerged. The most famous one is the genetic algorithm .