Abstract detail

336 / 2021-06-30 14:54:05
Rest Life Prediction of Rotating Machine Based on Manifold Algorithm and Time-varying Hidden-semi Markov Model
LLE; Feature fusion; TV-HSMM; RUL
Other related fields
Draft Paper Accepted
zhiyuan dong / Dalian University of Technology
The fault signal of rotating machinery contains a lot of useful information such as equipment degradation data, but the components are complex. This paper proposes a method of residual life prediction of rotating machinery based on manifold algorithm and time-varying hidden-semi Markov model pp(HSMM). The LLE algorithm is used to fuse the high dimensional features of the running signals of the equipment, and a new low dimensional fusion feature set which covers the linear and nonlinear information of the state signals is obtained. The hidden-semi Markov model is combined with the time-varying state transition probability matrix, and the residual life of rotating machinery is predicted according to the fusion feature set. Finally, the method is verified by the life cycle signal of rolling bearing.

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Important Dates

Abstract Submission Deadline:

 31st March 2021 15th April 2021

Extended Deadline: 1st Aug. 2022

 

Abstract Acceptance:

30th April  2021 Rollover

 

Full Paper Submission Deadline:

30th June 2021  14th July 2021

Extended Deadline: 15th Aug. 2022 

 

Notification of Acceptance:

15th August 2021 1st Sept. 2021

1st Sept. 2022

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