• 전기학회논문지
• /
• 제64권9호
• /
• pp.1347-1355
• /
• 2015

In this study, we compare the recognition performance using PCA and RBFNNs for introducing robust face recognition system to pose variations based on pose estimation. proposed face recognition system uses Honda/UCSD database for comparing recognition performance. Honda/UCSD database consists of 20 people, with 5 poses per person for a total of 500 face images. Extracted image consists of 5 poses using Multiple-Space PCA and each pose is performed by using (2D)²PCA for performing pose classification. Linear polynomial function is used as connection weight of RBFNNs Pattern Classifier and parameter coefficient is set by using Particle Swarm Optimization for model optimization. Proposed (2D)²PCA-based face pose classification performs recognition performance with PCA, (2D)²PCA and RBFNNs.

• 대한원격탐사학회지
• /
• 제10권2호
• /
• pp.49-62
• /
• 1994

Look direction bias in a single look SAR image can often be misinterpreted in the geological application of radar data. This paper investigates digital processing techniques for SAR image data integration and compensation of the SAR data look direction bias. The two important approaches for reducing look direction bias and integration of multiple SAR data sets are (1) principal component analysis (PCA), and (2) wavelet transform(WT) integration techniques. These two methods were investigated and tested with the ERS-1 (VV-polarization) and CCRS*s airborne (HH-polarization) C-SAR image data sets recorded over the Sudbury test site, Canada. The PCA technique has been very effective for integration of more than two layers of digital image data. When there only two sets of SAR data are available, the PCA thchnique requires at least one more set of auxiliary data for proper rendition of the fine surface features. The WT processing approach of SAR data integration utilizes the property which decomposes images into approximated image ( low frequencies) characterizing the spatially large and relatively distinct structures, and detailed image (high frequencies) in which the information on detailed fine structures are preserved. The test results with the ERS-1and CCRS*s C-SAR data indicate that the new WT approach is more efficient and robust in enhancibng the fine details of the multiple SAR images than the PCA approach.

• Smart Structures and Systems
• /
• 제32권5호
• /
• pp.281-295
• /
• 2023

The purpose of this study is to demonstrate and verify the application of phase-control absolute-acceleration-feedback active tuned mass dampers (PCA-ATMD) to multiple-degree-of-freedom (MDOF) building structures. In addition, servo speed control technique has been developed as a replacement for force control in order to mitigate the negative effects caused by friction and inertia. The essence of the proposed PCA-ATMD is to achieve a 90° phase lag for a structure by implementing the desired control force so that the PCA-ATMD can receive the maximum power flow with which to effectively mitigate the structural vibration. An MDOF building structure with a PCA-ATMD and a real-time filter forming a complete system is modeled using a state-space representation and is presented in detail. The feedback measurement for the phase control algorithm of the MDOF structure is compact, with only the absolute acceleration of one structural floor and ATMD's velocity relative to the structure required. A discrete-time direct output-feedback optimization method is introduced to the PCA-ATMD to ensure that the control system is optimized and stable. Numerical simulation and shaking table experiments are conducted on a three-story steel shear building structure to verify the performance of the PCA-ATMD. The results indicate that the absolute acceleration of the structure is well suppressed whether considering peak or root-mean-square responses. The experiment also demonstrates that the control of the PCA-ATMD can be decentralized, so that it is convenient to apply and maintain to real high-rise building structures.

• Journal of Electrical Engineering and Technology
• /
• 제13권4호
• /
• pp.1614-1622
• /
• 2018

The research related to fault diagnosis in permanent magnet synchronous motors (PMSMs) has attracted considerable attention in recent years because various faults such as permanent magnet demagnetization and short-circuited turns can occur and result in unexpected failure of motor related system. Several conventional current and back electromotive force (BEMF) analysis techniques were proposed to detect certain faults in PMSMs; however, they generally deal with a single fault only. On the contrary, cases of multiple faults are common in PMSMs. We propose a fault diagnosis method for PMSMs with single and multiple combined faults. Our method uses three phase BEMF voltages based on the fast Fourier transform (FFT), support vector machine(SVM), and visualization tools for identifying fault types and severities in PMSMs. Principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) are used to visualize the high-dimensional data into two-dimensional space. Experimental results show good visualization performance and high classification accuracy to identify fault types and severities for single and multiple faults in PMSMs.

• 환경영향평가
• /
• 제27권4호
• /
• pp.353-366
• /
• 2018

본 연구의 목적은 임진강 수질오염총량관리제도를 위한 단위유역의 2012년 1월부터 2016년 12월까지 유량과 수질자료를 통계분석기법에 이용하여 수질특성을 평가하는 것이다. 유량과 수질은 평균 8일 간격으로 측정하였으며 11개 항목을 상관분석, 주성분 분석, 요인분석, 군집분석에 사용하였다. 군집분석의 결과 공간변화에 따라 자연형 하천, 도시형 하천, 점오염원 영향이 큰 지점 등으로 3개의 그룹으로 분류되었으며, 오염원의 종류와 수질 유사성이 군집 분류에 영향을 미치는 것으로 나타났다. 일원 분산분석과 사후검정을 이용하여 군집간의 평균사이에는 통계적으로 유의한 수준의 차이가 있는 것으로 나타났다. 상관분석에서 $COD_{Mn}$와 TOC의 상관계수가 0.951(p<0.01)로 상관성이 통계적으로 유의하게 높게 나타났다. 주성분 분석 결과 3개의 주성분으로 전체 수질특성의 72%를 설명할 수 있으며 요인분석에서 주요 요인은 EC, $BOD_5$, $COD_{Mn}$, TN, TP, TOC 항목으로 나타나 유기물과 영양염류 간접지표가 수질에 영향을 미치는 것으로 나타났다. 본 연구에서 요인점수를 다중 선형회귀분석에 적용하여 회귀 방정식을 제시하고 임진강 유역 수질관리에 유기물 및 영양염류 간접지표 항목의 관리가 중요하다고 판단된다.