• Journal of Welding and Joining
• /
• v.18 no.5
• /
• pp.63-69
• /
• 2000

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables was wire feed rate, welding voltage, and welding speed and the output variables were bead height, bead width, and penetration. The number of level for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 40 experiments.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2003.05a
• /
• pp.520-525
• /
• 2003

The determination of unknown parameters in rotating machinery is a difficult task and optimization techniques represent an alternative technique for parameter identification. The Simulated Annealing(SA) and Genetic Algorithm(GA) are powerful global optimization algorithm. This paper proposes new hybrid algorithm which combined GA with SA and local search algorithm for the purpose of parameter identification. Numerical examples are also presented to verify the efficiency of proposed algorithm. And, this paper presents the general methodology based on hybrid algorithm to identify unknown bearing parameters of flexible rotors using measured unbalance responses. Numerical examples are used to ilustrate the methodology used, which is then validated experimentally.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.49 no.3
• /
• pp.85-94
• /
• 2000

In this paper, a robust H$\infty$ optimal tuning problem of a structure-specified PSS is investigated for power systems with parameter variation and disturbance uncertainties. Genetic algorithm is employed for optimization method of PSS parameters. The objective function of the optimization problem is the H$\infty$-norm of a closed loop system. The constraint of the optimization problem are based on the stability of the controller, limits on the values of the parameters and the desired damping of the dominant oscillation mode. It is shown that the proposed H$\infty$ PSS tuned using genetic algorithm is more robust than conventional PSS.

• Proceedings of the KIEE Conference
• /
• 2000.07b
• /
• pp.647-649
• /
• 2000

This paper presents a optimization procedure by using Response Surface Methodology(RSM) to determine design Parameters for reducing cogging torque in BLDC motor of Electric Power Steering (EPS). RSM is achieved through using the experiment design method in combination with Finite Element Method and well adapted to make analytical model for a complex problem considering a lot of interaction of these parameters. Moreover, Sequential Quadratic Problem (SQP) method is used to solve the resulting of constrained nonlinear optimization problem.

• Journal of the Korean Dietetic Association
• /
• v.15 no.4
• /
• pp.356-363
• /
• 2009

The study aimed to determine the optimal mixing ratio of two different amounts of Letinus edodes powder and egg for preparation of pasta. The complete analysis was conducted using the Design Expert 7 program (State-Easy, Minneapolis, MN). Response surface methodology revealed 10 experimental points, including two replicates for L. edodes powder and egg. L. edodes pasta formulation was optimized using rheology. Lightness and redness displayed a lineal model pattern, whereas yellowness was represented by a quadratic model. The sensory evaluation parameters of texture, color, flavor, appearance and overall quality showed significant differences for color (p<0.01), flavor (p<0.05), texture (p<0.05) and overall quality (p<0.05). All sensory parameters showed significant values in a quadratic model. The optimum formulations processed by numerical and graphical optimization were determined as 15 g of L. edodes powder and 37.5 g of egg.

• Journal of Microbiology
• /
• v.43 no.1
• /
• pp.38-43
• /
• 2005

Lactic acid production parameter optimization using Lactobacillus amylovorus NRRL B-4542 was performed using the design of experiments (DOE) available in the form of an orthogonal array and a software for automatic design and analysis of the experiments, both based on Taguchi protocol. Optimal levels of physical parameters and key media components namely temperature, pH, inoculum size, moisture, yeast extract, $MgSO_4{\cdot}7H_20$, Tween 80, and corn steep liquor (CSL) were determined. Among the physical parameters, temperature contributed higher influence, and among media components, yeast extract, $MgSO_4{\cdot}7H_20$, and Tween 80 played important roles in the conversion of starch to lactic acid. The expected yield of lactic acid under these optimal conditions was 95.80% and the actual yield at optimum conditions was 93.50%.

• Journal of Electrical Engineering and Technology
• /
• v.7 no.6
• /
• pp.948-953
• /
• 2012

The characteristics of an induction motor vary with the number of parameters and the performance relationship between the parameters also is implicit. In case of the induction motor design, we generally should estimate many objective physical quantities in the optimization procedure. In this article, the multi objective design optimization based on genetic algorithm is applied for the three phase induction motor. The efficiency, starting torque, and material cost are selected for the objectives. The validity of the design results is also clarified by comparison between calculated results and measured ones.

• Transactions of The Korea Fluid Power Systems Society
• /
• v.5 no.3
• /
• pp.1-8
• /
• 2008

The optimal design of a large-size fully hydraulic breaker is studied in this paper. Mathematical modeling of the breaker is established and verified by experiments. Through sensitivity analysis, the key design parameters of the breaker are selected, which mostly affect the performance of the breaker. Taguchi method is used to optimize the key design parameters in order to maximize the output power through simulation using AMESim. As a result, the impact energy is increased by 18.9% and the output power is increased by 12.4% compared with the current design. The pressure pulsation in the supply line is also reduced by the optimization.

• International Journal of Korean Welding Society
• /
• v.1 no.1
• /
• pp.44-50
• /
• 2001

A genetic algorithm was applied to the arc welding process as to determine the near-optimal settings of welding process parameters that produce the good weld quality. This method searches for optimal settings of welding parameters through the systematic experiments without the need for a model between the input and output variables. It has an advantage of being capable to find the optimal conditions with a fewer number of experiments rather than conventional full factorial designs. A genetic algorithm was applied to the optimization of the weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed. The output variables were the bead height bead width, and penetration. The number of levels for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions,2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions in less than 40 experiments.

• The Journal of Korea Robotics Society
• /
• v.18 no.4
• /
• pp.481-486
• /
• 2023

The purpose of this study is to optimize parameters of a contact model to obtain similar ground contact force of human walking. Dynamic walking simulation considering ground contact is performed to determine load specifications when developing walking assist robots. Large contact forces that are not observed in actual experimental data occur during the simulation at the initial contact (e.g., heel contact). The large contact force generates unrealistic large joint torques. A lower exoskeleton robot with no ankles is developed with the Matlab simscape and the nonlinear hyper volumetric contact model is applied. Parameters of the nonlinear hyper volumetric model were optimized using actual walking contact force data. As a result of optimization, it was possible to obtain a contact force pattern similar to actual walking by removing the large contact force generated during initial contact.