• Journal of KSNVE
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• v.9 no.2
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• pp.377-386
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• 1999

This paper is a study on model method for estimating system inputs from vibration responses, which is one of indirect input identification methods in frequency domain. The method has advantages over direct inverse method especially when points of operational inputs are inaccessible so that artificial excitation forces cannot be applied to obtain frequency response functions of the complete system. Procedures of extended modal model method are proposed and checked by numerical experiment. Mechanisms of error propagation, i.e., how errors in modal parameters such as poles nad mode shape vectors affect estimation of the input forces, are illustrated. Then, in order to counteract the error propagation, discrete modal filter approach is taken in this paper to compute the inversion of modal matrix in which the most serious errors seem to be generated. Further, a Reduced form of Modified Reciprocal Modal Vector(RMRMV) is proposed for estimating multiple inputs. It is shown to have smaller orthogonality error than MRMV.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.267-269
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• 1996

Servo systems became indispensable to applications such as industrial robots and numerically controlled machinery. Especially, induction motor drives are widely used as ac-servo system owing to the fact that it is maintenance-free. At the present time, Quick torque control methods such as vector control have been employed that enables an induction motor to attain as quick torque response as a dc motor. However, these methods can not be realized without knowing several motor parameters accurately, because the methods need them to calculate flux or voltage command. Most of all, secondary resistance has to be identified accurately, because it's value varies greatly for operation of induction motors. In this paper, a new identification method of secondary resistance based on quick torque control system of induction motors is proposed. The proposed method is derived theoretically from motor circuit equation and can be realized very simply by detecting primary current and voltage command of the motor. Through the numerical simulation considered using PWM inverter, the validity of the proposed method was successfully confirmed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.281-286
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• 2003

A Suspension system of a car is composed of dampers and springs. The dampers and springs usually have nonlinear characteristics. However, the nonlinear characteristics of the springs and dampers through analytical model cannot agree with the experimental results. Therefore, the nonlinearity of the suing and damper should be known from the experimental results. In this study, the methods of system identification for nonlinear dynamic system in time domain are discussed and the nonlinear parameter estimation lot experimental data of an EF-SONATA car was done. The results show that a cubic and a coupled term should be considered to model the suspension system.

• Journal of Oral Medicine and Pain
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• v.21 no.1
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• pp.37-54
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• 1996

In this thesis, a new superimposition scheme using a computer vision system was proposed with 7 pairs of skull and ante-mortem photographs, which were already identified through other tests and DNA fingerprints at the Korea National Institute of Scientific Investigation. At this computer vision system, an unidentified skull was caught by video-camcoder with the MPEG and a ante-mortem photograph was scanned by scanner. These two images were processed and superimposed using pixel processing. Recognition of the individual identification by anatomical references was performed on the two superimposed images. These results were as followings. 1. For the enhancement of skull and ante-mortem photographs, various image processing schemes, such as SMOOTH, SHARPEN, EMBOSS, MOSAIC, ENGRAVE, INVERT, NEON and COLOR TO MONO, were applied using 3*5 window processing. As an image processing result of these methods, the optimal techniques were NEON, INVERT and ENGRAVE for the edge detection of skull and ante-mortem photograph. 2. Using various superimposition image processing techniques (SRCOR, SRCAND, SRCINVERT, SRCERASE, DSTINVERT, MERGEPAINT) were compared for the enhancement of image recognition. 3. By means of the video camera, the skull image was inputed directly to a computer system : superimposing it on the ante-mortem photograph made the identification more precise and time-saving. As mentioned above, this image processing techniques for the superimposition of skull and ante-mortem photographs simply used the previous approach, In other wrods, taking skull photographs and developing it to the same size as the ante-mortem photographs. This system using various image processing techniques on computer screen, a more precise and time-saving superimposition technique could be able to be applied in the area of individual identification in forensic practice.

• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.252-260
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• 2022

Purpose: As the intensity and frequency of natural hazards are increasing due to climate change, external events that affecting nuclear power plants(NPPs) may increase. NPPs must be protected from external events such as natural hazards and human-induced hazards. External events that may occur in NPPs should be identified, and external events that may affect NPPs should be identified. This study introduces the methodology of identification and screening methods for external events by literature review. Method: The literature survey was conducted on the identification and screening methods of external events for probabilistic safety assessment of NPPs. In addition, the regulations on the identification and screening of external events were investigated. Result: In order to minimize the cost of external event impact analysis of nuclear power plants, research on identifying and screening external events is being conducted. In general, in the identification process, all events that can occur at the NPPs are identified. In the screening process, external events are selected based on qualitative and quantitative criteria in most studies. Conclusions: The process of identifying and screening external events affecting NPPs is becoming important. This paper, summarize on how to identify and screen external events for a probabilistic safety assessment of NPPs. It is judged that research on bounding analysis and conservative analysis methods performed in the quantitative screening process of external events is necessary.

• Smart Structures and Systems
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• v.5 no.4
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• pp.457-468
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• 2009

A novel approach for integrating active sensing data interrogation algorithms for structural health monitoring (SHM) applications is presented. These algorithms cover Lamb wave propagation, impedance methods, and sensor diagnostics. Contrary to most active-sensing SHM techniques, which utilize only a single signal processing method for damage identification, a suite of signal processing algorithms are employed and grouped into one package to improve the damage detection capability. A MATLAB-based user interface, referred to as HOPS, was created, which allows the analyst to configure the data acquisition system and display the results from each damage identification algorithm for side-by-side comparison. By grouping a suite of algorithms into one package, this study contributes to and enhances the visibility and interpretation of the active-sensing methods related to damage identification. This paper will discuss the detailed descriptions of the damage identification techniques employed in this software and outline future issues to realize the full potential of this software.

• Journal of Dairy Science and Biotechnology
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• v.30 no.2
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• pp.131-137
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• 2012

Rapid and reliable identification of microorganisms is a key for tracing the relationship between the target bacteria and related infectious diseases. Various identification methods such as classical phenotypic analysis, numerical taxonomic analysis, and DNA sequencing have been widely used to classify microorganisms in milk and dairy products. Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) identifies targeted bacteria in milk and milk products. Several studies have demonstrated that MALDI-TOF MS identification is an efficient and inexpensive method for the rapid and routine identification of isolated bacteria. MALDI-TOF MS could provide accurate identification of bacteria in milk and milk products at the serotype or strain level and enable antibiotic resistance profiling within minutes.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.555-565
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• 1999

The optimal identification algorithm of fuzzy systems is presented for rule-based fuzzy modeling of nonlinear complex systems. Nonlinear systems are expressed using the identification of structure such as input variables and fuzzy input subspaces, and parameters of a fuzzy model. In this paper, the rule-based fuzzy modeling implements system structure and parameter identification using the fuzzy inference methods and hybrid structure combined with two types of optimization theories for nonlinear systems. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. The proposed hybrid optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Here, a genetic algorithm is utilized for determining initial parameters of membership function of premise fuzzy rules, and the improved complex method which is a powerful auto-tuning algorithm is carried out to obtain fine parameters of membership function. Accordingly, in order to optimize fuzzy model, we use the optimal algorithm with a hybrid type for the identification of premise parameters and standard least square method for the identification of consequence parameters of a fuzzy model. Also, an aggregate performance index with weighting factor is proposed to achieve a balance between performance results of fuzzy model produced for the training and testing data. Two numerical examples are used to evaluate the performance of the proposed model.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1892-1896
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• 2005

In this paper, an effective method for selecting significant input variables in building ANFIS (Adaptive Neuro-Fuzzy Inference System) for nonlinear system modeling is proposed. Dominant inputs in a nonlinear system identification process are extracted by evaluating the performance index and they are applied to ANFIS. The availability of our proposed model is verified with the Box and Jenkins gas furnace data. The comparisons with other methods are also given in this paper to show our proposed method is superior to other models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.11
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• pp.1279-1289
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• 1992

Fault-tolerant system in improved the reliability and safety by using hardware and software redundancy. Fault mask and detection, identification techniques are conditionally used with system's application areas. Here DMR system is operated with standby and fail-safe module method that has minimal hardware and software redundancy, then its reliablity and safety comparison is presented respectively. Also this paper proposed an effective methods of dealing with transient faults as compared system's MTTFs to transient faults tolerance capabilities of self-diagnosis program.