NDLI: Integrated prognosis of AC servo motor driven linear actuator using Hidden Semi-Markov models

Content Provider	IEEE Xplore Digital Library
Author	Xin Wu Yaoyu Li Lundell, T.D. Guru, A.K.
Copyright Year	2009
Description	Author affiliation: Kinetix Motion Control, Rockwell Automation, 6950 Washington Eden Prairie, MN 55344, USA (Guru, A.K.) \|\| Kinetix Motion Control, Rockwell Automation, 6400 W. Enterprise Drive, Mequon, WI 53092, USA (Lundell, T.D.) \|\| Department of Mechanical Engineering, University of Wisconsin Milwaukee, 53201, USA (Xin Wu; Yaoyu Li)
Abstract	Motor prognosis has great benefit for motion control systems. It is desirable to develop the so-called integrated prognosis capability for motion control products, i.e. with only the existing sensors of a motor drive. This paper presents a scheme of integrated wear prognosis for linear actuators driven by AC servo motor with only current measurement. The Hidden Semi-Markov Model (HSMM) was adopted as the prognostic model. Compared to a single observation for a state in the hidden Markov model (HMM), a state in an HSMM generates a segment of observations. Therefore, HSMM structure has a temporal component. For the HSMM based prognostic model, the states correspond to different levels of health status. The duration of a health state is modeled by an explicit Gaussian probability function. To avoid the underflow of computation, the modified forward-backward training algorithm was used to estimate the model parameters. The expectation-modification method was used to estimate the state transition probability matrix, initial state distribution, and observation probability matrix in the model. The trained HSMMs can be used to predict the remaining-useful-life (RUL) on the actuator. The proposed method is demonstrated through the simulation of the wear process of an AC motor driven linear actuator.
Starting Page	1408
Ending Page	1413
File Size	560760
Page Count	6
File Format	PDF
ISBN	9781424442515
DOI	10.1109/IEMDC.2009.5075387
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Servomechanisms AC motors Servomotors Hydraulic actuators Hidden Markov models Motion control Motor drives Current measurement Parameter estimation State estimation
Content Type	Text
Resource Type	Article

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