Presentation 2011-03-10
Likelihood Histogram for Fault Detection
Masashi ANDO, Seiji HOTTA, Hisae SHIBUYA, Shunji MAEDA,
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Abstract(in English) This paper proposes a descriptor for multiple sensor sequences called likelihood histogram. In our descriptor, models are formed for individual sensors on each time using the Gaussian function. Through voting sensor values to them at each time, we obtain a histogram whose number of bins is equal to that of sensors. By using our descriptor, we can classify normal and fault days by commonly used classifiers such as support vector machine.
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Keyword(in English) multiple sensors / fault detection / likelihood histogram / pyramid representation
Paper # PRMU2010-259
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Conference Information
Committee PRMU
Conference Date 2011/3/3(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Likelihood Histogram for Fault Detection
Sub Title (in English)
Keyword(1) multiple sensors
Keyword(2) fault detection
Keyword(3) likelihood histogram
Keyword(4) pyramid representation
1st Author's Name Masashi ANDO
1st Author's Affiliation Tokyo University of Agriculture and Technology()
2nd Author's Name Seiji HOTTA
2nd Author's Affiliation Tokyo University of Agriculture and Technology
3rd Author's Name Hisae SHIBUYA
3rd Author's Affiliation Production Engineering Research Laboratory, Hitachi, Ltd.
4th Author's Name Shunji MAEDA
4th Author's Affiliation Production Engineering Research Laboratory, Hitachi, Ltd.
Date 2011-03-10
Paper # PRMU2010-259
Volume (vol) vol.110
Number (no) 467
Page pp.pp.-
#Pages 4
Date of Issue