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Title of Journal: Int J Adv Manuf Technol

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Abbravation: The International Journal of Advanced Manufacturing Technology

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Springer-Verlag

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DOI

10.1016/0010-440x(88)90049-1

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1433-3015

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Equipment health diagnosis and prognosis using hid

Authors: Ming Dong David He Prashant Banerjee Jonathan Keller
Publish Date: 2005/11/19
Volume: 30, Issue: 7-8, Pages: 738-749
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Abstract

In this paper the development of hidden semiMarkov models HSMMs for equipment health diagnosis and prognosis is presented An HSMM is constructed by adding a temporal component into the welldefined hidden Markov model HMM structures The HSMM methodology offers two significant advantages over the HMM methodology in equipment health diagnosis and prognosis 1 it overcomes the modeling limitation of HMM due to the Markov property and therefore improves the power in diagnosis and 2 it can be directly used for prognosis The application of the HSMMs to equipment health diagnosis and prognosis is demonstrated with the fault classification application of UH60A Blackhawk main transmission planetary carriers and prognosis of a hydraulic pump health monitoring application The effectiveness of the HSMMs is compared with that of the HMMs The results of the application testing have shown that the HSMMs are capable of identifying the faults under both test cell and onaircraft conditions while the performance of the HMMs is not comparable with that of the HSMMs Furthermore the HSMMbased methodology can be used to estimate the remaining useful life of equipment

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