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주성분분석을 이용한 인공위성 관성센서의 고장검출기법 연구 : Fault Detection Method of the Inertial Sensors in the Satellite Using Principal Component Analysis

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dc.contributor.authorLee, Wonhee-
dc.contributor.authorLim, Jun Kyu-
dc.contributor.authorPark, Chan Gook-
dc.date.accessioned2010-01-07T01:54:10Z-
dc.date.available2010-01-07T01:54:10Z-
dc.date.issued2009-11-06-
dc.identifier.citationThe 16th GNSS Workshopen
dc.identifier.urihttps://hdl.handle.net/10371/27783-
dc.description.abstractThis paper presents the fault detection method of the inertial sensors in the satellite attitude control system using PCA (Principal Component Analysis). Component analysis is an approach to finding the fault features from the data. PCA which is one of the pattern recognition methods detects the fault feature by projecting the high-dimensional inertial sensor data onto a lower dimensional space. In this paper, we suggest how to reduce the dimension of the sensor data to two-dimension. The method enables us to detect the faulty sensor by analyzing the pattern of projected sensor data.en
dc.description.sponsorshipNSLen
dc.language.isokoen
dc.subjectsatelliteen
dc.subjectinertial sensoren
dc.subjectPCAen
dc.subjectfaulten
dc.title주성분분석을 이용한 인공위성 관성센서의 고장검출기법 연구en
dc.title.alternativeFault Detection Method of the Inertial Sensors in the Satellite Using Principal Component Analysisen
dc.typeConference Paperen
dc.contributor.AlternativeAuthor이원희-
dc.contributor.AlternativeAuthor임준규-
dc.contributor.AlternativeAuthor박찬국-
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