• 대한전기학회:학술대회논문집
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• 대한전기학회 1989년도 하계종합학술대회 논문집
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• pp.12-15
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• 1989

This paper describes the efforts to develop an PC based parameter identification system for the D.C. servomotor. The whole identification process of signal generation, measuring, parameter determination is fully automated. To minimize errors due to the ripple component in the measured armature current, digital averaging filter is employed. The proposed parameter correction method using the deadzone current and the time to reach the peak current resulted in excellent agreement between the measured current and estimated current using the model.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.109.6-109
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• 2002

In this paper, the scheme of fuzzy system construction using GA(genetic algorithm) and FCM(Fuzzy c-means) clustering algorithm is proposed for TSK(Takagi-Sugeno-Kang) type fuzzy system. in the structure identification, input data is trans-formed by PCA(Principal Component Analysis) to reduce the correlation among input data components. And then, the number of fuzzy rule is obtained by a given performance criterion. In the parameter identification, the premise parameters are optimally searched by GA. On the other hand, the consequent parameters are estimated by RLSE(Recursive Least Square Estimate) to reduce the search space. From this, one can systematically obtain optimal parameter and the v..

• 한국정밀공학회지
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• 제9권3호
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• pp.29-41
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• 1992

According to the recent increase of demands for multi-function and economics on hydraulic excavator, it is required that excavator should have simple operation, higher and operational efficiency, however the modeling of engine/pump system of excavator is not prescribed by the paper. So, in this paper the modeling of engine/pump system of excavator is suggested by identification method from step response and verified effectiveness of identification system by comparing with experimental results which was conducted using PID controller. To improve the problem of parameter variation and modeling error in the system, sliding mode control was introduced and new switching surface was designed. This control algorithm was applied to a hydraulic excavator by simulation, and its effectiveness was verified, and the results of variable structure system for the excavator system using a output component was compared with that of full state feedback when load disturbances and system paramenter variation exist.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2007년도 한국음성과학회 공동학술대회 발표논문집
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• pp.319-322
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• 2007

The goal of our research is to build a textindependent speaker identification system that can be used in mobile devices without any additional adaptation process. In this paper, we show that exploiting the advantages of both PCA(Principle Component Analysis) and LDA(Linear Discriminant Analysis) can increase the performance in the situation. The proposed method reduced the relative recognition error by 13.5%

• 한국소음진동공학회논문집
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• 제14권10호
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• pp.930-938
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• 2004

This paper presents the noise source identification of a car A/V system. There are two different kinds of noise sources noise generated by loading mechanism and rattle noise by externally forced vibration. A dynamometer has been made to produce stationary inertia to the loading mechanism of A/V system. Sound pressure spectra and sound intensity were measured by operating the dynamometer setup as various motor speeds, and the results were analyzed. A dominant rattle noise source about A/V system's components has been found by multi-dimensional spectral analysis. Residual spectrum method was applied for eliminating coherence between the vibration sources. In result, the dominant rattle noise source was identified by partial coherent output spectrum of individual vibration component.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1674-1677
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• 2002

In this paper, the new method to extract the features of iris signals is proposed; Multiresolution ICA (M-ICA) provides good properties to represent signals with time-frequency. The conventional methods were to use the technique of filter bank analysis, while ICA is unsupervised learning algorithm using high-order statistics. M-ICA could make use of strengths of learn- ing method and multiresolution. Also, we performed comparative studies of different feature extraction techniques applied to personal identification using iris pat- tern. To measure goodness of methods, we use Fisher’s discriminant ratio to quantify the class-separability of features generated by various techniques.

• Journal of Ship and Ocean Technology
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• 제7권3호
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• pp.56-65
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• 2003

The hull monitoring systems of container ships with four long-base gages give enough information for identifying the hull girder loads such as bending and torsional moments. But such a load-identification for container ships has not been known. In this paper, a load-identification method is suggested in terms of a linear matrix equation that the measured strain vector equals to the multiplication of the transformation matrix and the desired strain component vector. The equation is proved to be mathematically complete by the property of positive-definite determinant of the transformation matrix. The method is applied to a hull stress monitoring system for 8100TED container ship during sea trial, and the estimated external loads illustrate reasonable results in comparison with the pre-estimated results. This moment decomposition concept has also been tested in real operation conditions. The typical phenomena over the Suez Canal illustrated very suitable results comparing with the physical understandings. Henceforth, one can effectively use the proposed concept to monitor the hull girder loads such as bending and torsional moments.

• Journal of Microbiology and Biotechnology
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• 제25권8호
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• pp.1257-1264
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• 2015

Trichoderma strain T-33 has been demonstrated to have inhibitory effect on the fungus species Cytospora chrysosperma. Here, an active antifungal compound was obtained from Trichoderma strain T-33 extract via combined separation technologies, including organic solvent extraction, liquid chromatography, and thin-layer chromatography. The purified compound was further characterized by advanced analytical technologies to elucidate its chemical structure. Results indicated that the active antifungal compound in Trichoderma strain T-33 extract is 2,5-cyclohexadiene-1,4-dione-2,6-bis (1,1-dimethylethyl).

• 대한안전경영과학회지
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• 제15권3호
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• pp.105-112
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• 2013

To meet the growing needs from a variety of stakeholders, the development of modern systems is getting more complex and thus, the systems failure in the actual operations can potentially become more serious. This is why several international or military standards on systems safety have been published. In spite of the importance of meeting those standards such as IEC 61508 and ISO 26262 in the systems development, the associated practical methods seem deficient since those standards do not provide them. The objective of this paper is to present a method to identify potential hazards in fulfilling the requirements of the safety standards. In particular, the approach taken here is based on applying the functional analysis that covers several levels of the system under development. Note, however, that in the most of the conventional methods for hazards identification, the analysis has been focused on the failure at or underneath the component level of the system. The hazards identification method in this paper would cover the level up to the system by utilizing the functions-oriented approach. The case study of the safety enhancement for locomotive cabs is also discussed.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1406-1416
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• 2017

In complex and large-scale industries, properly designed fault detection and identification (FDI) systems considerably improve safety, reliability and availability of target processes. In thermal power plants (TPPs), generating units operate under very dangerous conditions; system failures can cause severe loss of life and property. In this paper, we propose a bagged auto-associative kernel regression (AAKR)-based FDI approach for steam boilers in TPPs. AAKR estimates new query vectors by online local modeling, and is suitable for TPPs operating under various load levels. By combining the bagging method, more stable and reliable estimations can be achieved, since the effects of random fluctuations decrease because of ensemble averaging. To validate performance, the proposed method and comparison methods (i.e., a clustering-based method and principal component analysis) are applied to failure data due to water wall tube leakage gathered from a 250 MW coal-fired TPP. Experimental results show that the proposed method fulfills reasonable false alarm rates and, at the same time, achieves better fault detection performance than the comparison methods. After performing fault detection, contribution analysis is carried out to identify fault variables; this helps operators to confirm the types of faults and efficiently take preventive actions.