• Smart Structures and Systems
• /
• v.8 no.4
• /
• pp.343-365
• /
• 2011

Structural system identification (SSI) is an inverse problem of difficult solution. Currently, difficulties lie in the development of algorithms which can cater to large size problems. In this paper, a parameter estimation technique based on evolutionary strategy is presented to overcome some of the difficulties encountered in using the traditional system identification methods in terms of convergence. In this paper, a non-traditional form of system identification technique employing evolutionary algorithms is proposed. In order to improve the convergence characteristics, it is proposed to employ immune algorithms which are proved to be built with superior diversification mechanism than the conventional evolutionary algorithms and are being used for several practical complex optimisation problems. In order to reduce the number of design variables, domain decomposition methods are used, where the identification process of the entire structure is carried out in multiple stages rather than in single step. The domain decomposition based methods also help in limiting the number of sensors to be employed during dynamic testing of the structure to be identified, as the process of system identification is carried out in multiple stages. A fifteen storey framed structure, truss bridge and 40 m tall microwave tower are considered as a numerical examples to demonstrate the effectiveness of the domain decomposition based structural system identification technique using immune algorithm.

• Korean Journal of Construction Engineering and Management
• /
• v.4 no.2 s.14
• /
• pp.109-117
• /
• 2003

The construction project is largely exposed to much more risk events over the project life cycle due to its complexity and size than the other industries. Therefore, the construction risk management process to identify and response the risk events is not only performing acutely but also proceeding systematically. The risk identification phase in the risk management process is to identify various risk events and define its characteristics. At this phase, the risk identification system is very useful tool to identify every possible risk events in the project. This study shows some problems of the existing risk identification system and proposes the modified risk identification system based on the project phases and the contract bodies, and also suggests partial but more enough detailed risk checklists to be implemented in the actual risk identification phase than any other existing risk breakdown systems to be examined at this study.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.10
• /
• pp.1293-1302
• /
• 1999

In this paper, an on-line process scheme is presented for implementation of a intelligent on-line modeling of nonlinear complex system. The proposed on-line process scheme is composed of FNN-based model algorithm and PLC-based simulator, Here, an adaptive fuzzy-neural networks and HCM(Hard C-Means) clustering method are used as an intelligent identification algorithm for on-line modeling. The adaptive fuzzy-neural networks consists of two distinct modifiable sturctures such as the premise and the consequence part. The parameters of two structures are adapted by a combined hybrid learning algorithm of gradient decent method and least square method. Also we design an interface S/W between PLC(Proguammable Logic Controller) and main PC computer, and construct a monitoring and control simulator for real process system. Accordingly the on-line identification algorithm and interface S/W are used to obtain the on-line FNN model structure and to accomplish the on-line modeling. And using some I/O data gathered partly in the field(plant), computer simulation is carried out to evaluate the performance of FNN model structure generated by the on-line identification algorithm. This simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy and feasibility than other works achieved previously.

• Nuclear Engineering and Technology
• /
• v.55 no.7
• /
• pp.2642-2649
• /
• 2023

A real-time unmeasured dynamic response prediction process for the nuclear power plant pressure pipeline is proposed and its performance is tested in the test-loop system (KAERI). The aim of the process is to predict unmeasurable or unreachable dynamic responses such as acceleration, velocity, and displacement by using a limited amount of directly measured physical responses. It is achieved by combining a well-constructed finite element model and robust inverse force identification algorithm. The pressure pipeline system is described by using the displacement-pressure vibro-acoustic formulation to consider fully filled liquid effect inside the pipeline structure. A robust multiphysics modal projection technique is employed for the real-time sensor synchronized prediction. The inverse force identification method is also derived and employed by using Bathe's time integration method to identify the full-field responses of the target system from the modal domain computation. To validate the performance of the proposed process, an experimental test is extensively performed on the nuclear power plant pressure pipeline test-loop under operation conditions. The results show that the proposed identification process could well estimate the unmeasured acceleration in both frequency and time domain faster than 32,768 samples per sec.

• Korean Chemical Engineering Research
• /
• v.61 no.1
• /
• pp.89-96
• /
• 2023

The Wiener-type nonlinear model where a static nonlinear block follows a dynamic linear block is widely used to describe the dynamics of chemical processes. A long process excitation step is typically needed to identify this Wiener-type nonlinear model with two blocks. In order to cope with this disadvantage, an identification method for the Wiener-type nonlinear model that uses only a single-step response is proposed here. The proposed method estimates the response of the dynamic linear sub-block from the initial part of the step response, and then the static nonlinear sub-block is identified. Because the only single-step response is used to identify the Wiener-type nonlinear model, there is great benefit in time and cost for obtaining process response. The performance of the proposed identification method with the single-step response is verified through a representative Wiener-type nonlinear process, a pH titration process, and a liquid level system.

• The Research Journal of the Costume Culture
• /
• v.24 no.4
• /
• pp.417-430
• /
• 2016

This study had two aims. First, the study intended to identify the influences of product benefits and product identification on consumers' purchase intention, Second, it wanted to assess the moderating effects of consumers' aesthetic seeking tendency on their decision-making process. Based on the stimulus-organism-response (S-O-R) paradigm and the product personality-brand identification-purchase intention model, this study proposed a research model, the benefits-product identification-purchase intention model. To test the model, a survey was conducted of female college students; a total of 298 questionnaires were analyzed. The stimulus used was a popular model of Nike running footwear: the Luna Eclipse+2. Factor analysis and structural equation analysis were conducted to analyze the research model. The results indicate : (1) The aesthetic benefit influenced product identification positively. The aesthetic benefit, functional benefit and product identification were all positively related to purchase intention. (2) The aesthetic seeking tendency mediated the influences of product benefits on consumers' purchase intention in the decision-making process. For consumers in the 'high' level group of aesthetic seeking tendency, aesthetic benefit and social benefit affected purchase intention and for consumers in the 'low' level group of aesthetic seeking tendency, the functional benefit only affected purchase intention. Based on this study, we find evidence that product benefits and aesthetic seeking tendency play important roles in consumers' decision-making process in product purchase.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.53 no.4
• /
• pp.221-225
• /
• 2004

This paper shows the application of artificial intelligence technique such as polynomial neural network in modeling and identification of sequencing batch reactor (SBR). A wastewater treatment process for nitrogen removal in the SBR is presented. Simulation results have shown that the nonlinear process can be modeled reasonably well by the Present scheme which is simple but efficient.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.5 no.4
• /
• pp.303-311
• /
• 1981

Machine tool dynamics is investigated under actual working conditions. Experimental evaluation of cutting dynamics in a lathe is made with cutting conditions and cutting positions varied. The thrust force and the toolpost and tailstock accelerations during turning process are modelled and analyzed by employing Dynamic Data System methodology. It is found that two acceleration signals are good enough to replace the thrust force, when used for machine tool identification under cutting process and for chatter detection.

• International journal of advanced smart convergence
• /
• v.4 no.2
• /
• pp.84-93
• /
• 2015

This study is for the development of Cover Glass Grinding Processing System. This system is developed for manufacturing a mass product system grinding cover glasses with highly precise mechanism, and we improved resulted quality. In the development process, we developed a complete process technology through mechanical design, image processing technology, spindle control, mark identification algorithm etc. With this cover glass grinding development, we could developed process technology, image processing technology, organization mechanisms and control algorithms.

• Journal of the Korea Safety Management & Science
• /
• v.17 no.2
• /
• pp.1-11
• /
• 2015

Enterprise Risk Management(ERM) is aiming at the establishment of the risk management process to prevent and cope with risks in advance and is composed of Risk Identification, Risk Assessment, Risk Response and Monitoring. It is feedback through the Risk Re-identification. This study has analysed a sample of the risk management system of an airport operating corporation, for this purpose, relevant documents and examples of overseas airports have been reviewed. It has found that corporations establishing ERM have been performing identical procedures such as the process of Identification, Assessment, Effective Reporting, Communication and monitoring and so on. The A corporation has established the process for risk management and crisis management and organized for its organization and system. The risk management has the same process such as above. In this process, when the symptoms of critical crisis have been recognized, it has been transformed into crisis management system, through which, corporate-wide response has been conducted in the process of crisis status analysis, response and follow-up management. This study expects to contribute to systematic foundation for future business continuity on the basis of risks and response procedures acknowledged by this study.