• Journal of the Optical Society of Korea
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• v.7 no.2
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• pp.84-88
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• 2003

A new method for temperature compensation of fiber Bragg grating (FBG) using hi-metal is proposed and experimentally demonstrated. Bi-metal bends toward the metal of low temperature expansion coefficient as the temperature increases, and this property is utilized to cancel the thermo-optic effect of the fiber. The optimum thickness of the high coefficient metal was empirically found by the trial-and-error method. The temperature sensitivities were 8.1 pm/$^{\circ}C$ and -0.018 pm/$^{\circ}C$ for the uncompensated and compensated FBGs, respectively, which indicates a reduction to a mere 0.22 % of the original sensitivity. No appreciable change in the spectral shape was observed. The packaging technique described in this paper is simple and compact, and it can be used for FBGs in WDM and DWDM communication systems that have stringent requirements on the temperature stability of the components.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1996.10a
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• pp.142-147
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• 1996

For prediction and control of sound, acoustic systems must be modeled. Because sound systems like exhaust systems are very difficult to calculate mathematically, this study presents a method to determine experimentally the order of poles by transfer function. When designing a control system by traditional methods the exact model order and coefficient of the system to be controlled must be determined. But in acoustic systems, where systems to be controlled are very complex, mathematical interpretation is almost always impossible. Therefore transversal filters using trial and error methods to determine model order of a system are used to design a system. Compared to mathematical models with poles, transversal filters, in which the model order becomes relatively large, have the disadvantage of prolonged processing time and marked time delay. This study presents a method to determine experimentally the order of poles in a system model with poles and zeroes. Also, the validity of this method was verified mathematically and confirmed by application in general simple models and acoustic tube simulators.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.200-205
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• 1992

The classical control theory has been developed successfully for the design of a system controller and has evolved continually. Even though sophisticated simulation techniques and software packages are available, there is still some difficulty in the design of a complex system controller at the desk. So the trial and error method is sometimes used to design a new controller, but it requires excess time and cost. This paper suggests a controller design method through the experimental approach. The basic concept is to adjust gradually the design parameters of the controller to the simulation results and experimental data of a similar real system. This method will be a very useful and easy way to design an accurate and/or optimal controller for a real plant while reducing time and giving a good solution at a reasonable cost.

• BMB Reports
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• v.30 no.1
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• pp.7-12
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• 1997

The kinetics of the interesterification of triolein and stearic acid catalyzed by immobilized Rhizopus delemar lipase were studied in a batch operation. In order to clarify the mechanisms of this reaction, three models are discussed under various conditions in terms of the ratio of triolein and stearic acid. The rate constants involved in the proposed model were determined by combining the numerical Gauss-elemination method, and the trial-and-error method so as to fit the calculated results with the experimental data. The accuracy of the obtained rate constants was confirmed after they were substituted for simultaneous differential equations and the equations simulated using an adaptive step-size Runge-Kutta method. Finally, the model which agrees with the calculated results and the experimental data was selected.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.433-438
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• 2004

The rapid machining of prototypes plays an important role in product process. Rapid Prototyping(RP) is the widespread technology to produce prototype. But, it have many problems such as shrinkage, deformation and formation occurred by hardening of resin and stair shaping, On the contrary, high speed machining(HSM) technology has many advantages such as good quality, low cost and rapid machining time. Moreover, it is possible to use the material of original product. This paper presents manufacture of trial product by HSM and optimization of machining condition for high productivity in the view of manufacturing time and average error. For example, propeller is machined by the surface machining of thin surface parts. Experiments are designed of machining conditions by Latin Square method and machining condition is optimized and selected by ANOVA

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.8
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• pp.914-921
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• 1992

In this paper, we introduce a Walsh network and an LMS algorithm, and show how these can be realized as an adaptive equalizer. The Walsh network is built from a set of Walsh and Block pulse functions. In the LMS algorithm, the convergence factor is an important design parameter because it governs stability and convergence speed, which depend on the proper choice of the convergence facotr. The conventional adaptation techniques use a fixed time constant convergence factor by the method of trial and error. In this paper, we propose an optimal method in the choice of the convergence factor. The proposed algorithm depends on the received signal and the output of the Walsh network in real time.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.87-95
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• 1996

A new design scheme for the fuzzy pattern matching classifier (FPMC) is proposed. in conventional design of FPMC, there are no exact information about the membership function of which shape and number critically affect the performance of classifier. So far, a trial and error or heuristic method is used to find membership functions for the input patterns. But each of them have limits in its application to the various types of pattern recognition problem. In this paper, a new method to find the appropriate shape and number of membership functions for the input patterns which minimize classification error is proposed using genetic algorithms(GAs). Genetic algorithms belong to a class of stochastic algorithms based on biological models of evolution. They have been applied to many function optimization problems and shown to find optimal or near optimal solutions. In this paper, GAs are used to find the appropriate shape and number of membership functions based on fitness function which is inversely proportional to classification error. The strings in GAs determine the membership functions and recognition results using these membership functions affect reproduction of next generation in GAs. The proposed design scheme is applied to the several patterns such as tire tread patterns and handwritten alphabetic characters. Experimental results show the usefulness of the proposed scheme.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.7
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• pp.66-77
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• 1997

This paper presents an automatic tuning method for parameters of a multivaiable self-tuning velocity-type PID controller which adapts to changes in the system parameters with time delays and noises. The velocity-type PID control structure is determined in the process of minimizing the variance of the auxiliarly output, and self-tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optiminzing the design parameters of the controller. The proposed PID type multivariable self-tuning method is simple andeffective compared with other esisting multivariable self-tuning methods. Computer simulation has shown that the proposed algorithm is beter than the trial-and-error method in the tracking performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.233-236
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• 2007

A new evolution method for strong exploration and strong exploitation termed queen-bee and mutant-bee evolution is proposed based on the previous queen-bee evolution [1]. Even though the queen-bee evolution has shown very good performances, two parameters for strong mutation are added to the genetic algorithms. This makes the application of genetic algorithms with queen-bee evolution difficult because the values of the two parameters are empirically decided by a trial-and-error method without a systematic method. The queen-bee and mutant-bee evolution has no this problem because it does not need additional parameters for strong mutation. Experimental results with typical problems showed that the queen-bee and mutant-bee evolution produced nearly similar results to the best ones of queen-bee evolution even though it didn't need to select proper values of additional parameters.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.366-371
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• 2002

Because of the environmental problems, automotive companies are trying to reduce the weight of car body. Therefore, TRIP(TRansformation Induced Plasticity) steels, which have high strength and ductility have been developed. Welding process is a complex process; therefore deciding the optimal welding conditions on the basis of experimental data is an effective method. However, trial-and-error method to decide the optimal conditions requires too many experiments. To overcome these problems, response surface methodology was used. Response surface methodology is a collection of mathematical and statistical techniques that are used in the modeling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. This method was applied to the resistance spot welding process of the TRIP steel to optimize the welding parameters.