• Journal of Drive and Control
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• v.19 no.2
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• pp.11-16
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• 2022

It is important to measure the excavator's work productivity that estimates the bucket's payloads on a process. If the bucket isn't filled at every working cycle, the excavator's operator has to drive the machine more to achieve his work quota. If bucket is filled over with the load, the other way around, the transferred object has to spread out on the workplace. That causes additional work to clean the site. This paper proposes a method that can estimate the bucket's payload to improve the excavator's work productivity. This method assumes that the excavator is a lumped mass system. And it uses a 3 points angle (boom link, arm link, swing) and 2 points pressure (boom cylinder's input port and output port) of measurable data. Depending on assumptions, the bucket's payload can be calculated by the payload's motion equation. And this suggested method can be verified by simple experiments.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.6
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• pp.716-722
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• 2014

In order to design the speed controller of the DC motor system, firstly, parameters estimation of the system must be preceded. In this paper, we proposed the application of genetic algorithm(GA) optimization in estimating the parameters of DC motor. Estimated models are considered both first and second order models, and each estimated model is optimized by minimizing three different types of the evaluation function of GA. Also, GA is imported in comparison with estimation result of numerical analysis method because of its power in searching entire solution space with more probability of finding the global optimum. Data for parameter estimation is acquired from input and output signals of the actual experiment device and the butterworth filter also designs for removing noise in the signals. Finally comparison between real data of the actual device and estimated models is presented to indicate effectiveness and resolution of proposed identification method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.5
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• pp.303-310
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• 2020

In this study, a method for selection of the location and number of monitoring sensors in a building structure using artificial neural networks is proposed. The acceleration-history values obtained from the installed accelerometers are defined as the input values, and the mass and stiffness values of each story in a building structure are defined as the output values. To select the installation location and number of accelerometers, several installation scenarios are assumed, artificial neural networks are obtained, and the prediction performance is compared. The installation location and number of sensors are selected based on the prediction accuracy obtained in this study. The proposed method is verified by applying it to 6- and 10-story structure examples.

• Smart Structures and Systems
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• v.15 no.1
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• pp.151-167
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• 2015

Instrumentation on structural health monitoring system imposes critical issues for applying the structural monitoring system to real world structures, for which not only on the configuration and geometry, but also aesthetics on the system to be monitored should be considered. To illustrate this point, two real world structural health monitoring systems, the structural health monitoring system of Shenzhen Vanke Center and the structural health monitoring system of Shenzhen Bay Stadium in China, are presented in the paper. The instrumentation on structural health monitoring systems of real world structures is addressed by providing the description of the structure, the purpose of the structural health monitoring system implementation, as well as details of the system integration including the installations on the sensors and acquisition equipment and so on. In addition, an intelligent algorithm on stress identification using measurements from multi-region is presented in the paper. The stress identification method is deployed using the fuzzy pattern recognition and Dempster-Shafer evidence theory, where the measurements of limited strain sensors arranged on structure are the input data of the method. As results, at the critical parts of the structure, the stress distribution evaluated from the measurements has shown close correlation to the numerical simulation results on the steel roof of the Beijing National Aquatics Center in China. The research work in this paper can provide a reference for the design and implementation of both real world structural health monitoring systems and intelligent algorithm to identify stress distribution effectively.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.271-271
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• 2019

Estimating ship motion is difficult because it take place in complex environments.. Estimating ship motion is an important factor in ensuring the safety of ship, so accurate estimates are needed. Existing motion-related studies compare the apparent motion of the model acquired and the reference model by experimenting with the ship motion on a particular alignment, making it difficult to intuitively estimate the hull motion. This study introduces the concept of estimating the characteristics of ship motion as a transfer function through pole-zero interpretation and frequency response analysis by applying the method of transfer function of Linear-Time Invariant system. Ship motion analysis model using Linear-Time Invariant system is consist with 1) wave as input signal 2) ship motion as output signal 3) hull defined as black box. This model can be defined by numericalizing the ship motion as a transfer function and is expected to facilitate the characterization of the ship motion through pole-zero analysis and frequency response analysis.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.843-849
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• 2003

Web usage mining is the technique of data mining that analyzes web users' usage patterns by large web log. To use the web usage mining technique, we have to classify correctly users and users session in preprocessing, but can't classify them completely by only log files with standard web log format. To classify users and user session there are many problems like local cache, firewall, ISP, user privacy, cookey etc., but there isn't any definite method to solve the problems now. Especially local cache problem is the most difficult problem to classify user session which is used as input in web mining systems. In this paper we propose a heuristic method which solves local cache problem by using only click stream data of server side like referrer log, agent log and access log, classifies user sessions and completes session.

• Journal of the Korea Safety Management & Science
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• v.17 no.2
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• pp.129-137
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• 2015

This study is in regard to the gas detection system and gas detection method utilizing smart phone. This study includes; 1) the sensor module attached to the smart phone to detect and measure flammable gas or toxic gas; and 2) gas detection APP which is installed inside the smart phone and recognizes the user information and location information automatically by reading RFID tag indicating the user or the location to detect gas through the contact area where RFID and blue tooth reader is installed inside of the above mentioned smart phone, and then measures the combustible gas or toxic gas by operating above mentioned sensor module and obtains the data thus measured, and above mentioned smart phone is characterized by its transmission of the above mentioned user information, location information and measured data which are obtained by above mentioned gas detecting APP to operation server via communication network. With this, reliability for the location detecting gas by the user, the result of the measurement, etc. can be secured. Furthermore, this provides the effect of preventing artificial manipulation at the time of input which is associated with the identification of the user to be measured by utilizing removable sensor module and application or the mistake resulted from wrong input by the user. In addition, by transmitting the measured data from the sensor module carrying out gas detection to operation server, this provides the effect of making it possible to process the data thus collected to a specialized data for combustible gas or toxic gas.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.2
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• pp.126-135
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• 2002

The study is concerned with an approach to the design of new architectures of fuzzy neural networks and the discussion of comprehensive design methodology supporting their development. We propose an Adaptive Fuzzy Polynomial Neural Networks(APFNN) based on Fuzzy Neural Networks(FNN) and Self-organizing Networks(SON) for model identification of complex and nonlinear systems. The proposed AFPNN is generated from the mutually combined structure of both FNN and SON. The one and the other are considered as the premise and the consequence part of AFPNN, respectively. As the premise structure of AFPNN, FNN uses both the simplified fuzzy inference and error back-propagation teaming rule. The parameters of FNN are refined(optimized) using genetic algorithms(GAs). As the consequence structure of AFPNN, SON is realized by a polynomial type of mapping(linear, quadratic and modified quadratic) between input and output variables. In this study, we introduce two kinds of AFPNN architectures, namely the basic and the modified one. The basic and the modified architectures depend on the number of input variables and the order of polynomial in each layer of consequence structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the AFPNN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed AFPNN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• Journal of Navigation and Port Research
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• v.44 no.3
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• pp.145-150
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• 2020

The ship motion of large LNG ships affects ships' safety. The purpose of this study was to estimate the transfer function of roll motion among the hull motion of 153,000 m3 class LNG vessels. The ship motion transfer function was modeled using a Linear Time-Invarient system with single input, single output, and transfer function. The transfer function of the ship motion was estimated by the system identification method using single ocean wave as input of the model, and using the roll motion of the LNG ship obtained through ANSYS as the output of the model. The usefulness of the experimental results was evaluated using the precision and estimation rate of the model for cases wherein the different transfer function dimensions. Results of the experiment showed a precision at 99% and 98%, with estimation rate at 78% and 50%. From these results, we found the proposed method of estimating the transfer function of ship motion in this study reasonable. In the future, data of ship motion in actual sea conditions will be acquired and it will be applied to make the construction of models with multiple inputs and multiple outputs for practical use.

• Economic and Environmental Geology
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• v.39 no.6 s.181
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• pp.787-801
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• 2006

Focused in the characteristic of R&D on Geoscience and Mineral Resources as basic research area, we survey on methods of public works' economic impact analysis including cost-benefit analysis and resent technology evaluation methods and suggest apply-methods to conduct economic impact analysis on R&D of geoscience and mineral resources. To conduct economic impact analysis on the basic research area, it need to identification research's out-come not just output. In this perspective, we propose a method, Input-Output-Outcome Roadmapping to identify the outcome of R&D and show the relation of input, output, and outcome of R&D. Furthermore, noticing the different effects of R&D from public works, we directly evaluate the use-value of the academic theory or geological maps through Contingent Valuation Method(CVM) and others developed as evaluation methods on environmental goods. In indirect application methods, it can evaluate the partial of the pubic works' benefit with assuming R&D factors if R&D is a part of public works. If not, we evaluate the R&D's value as reductions of costs or additions of benefit with finding related public works.