[Poster Presentation]A multi-source domain generalization method for bearing RUL prediction based on time-variant and time-invariant feature extraction - International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence ((ICSMD2024))

A multi-source domain generalization method for bearing RUL prediction based on time-variant and time-invariant feature extraction

ID：112 Submission ID：8 View Protection：ATTENDEE Updated Time：2024-10-23 10:00:24 Hits：22 Poster Presentation

Start Time：Pending （Asia/Shanghai）

Duration：Pending

Session：[No Session] » [No Session Block]

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Abstract

Deep learning-based remaining useful life (RUL)

prediction methods have demonstrated significant advantages

due to their powerful feature representation capabilities. How

ever, existing learning models struggle to effectively distinguish

between the time-varying and time-invariant characteristics of

vibration signals, which hinders their generalization perfor

mance. To address this issue, we propose a domain generalization

method based on the extraction of time-varying and time

invariant features, tailored to the characteristics of bearing

vibration time series signals. Firstly, Fourier transform and

inverse Fourier transform are employed to isolate high-frequency

features, obtaining both time-varying and time-invariant signals.

The time-varying signals are then processed using an attention

mechanism to extract time-varying features and learn the bearing

degradation trend. Concurrently, the time-invariant signals are

fed into an encoder-decoder structure to extract their invariant

features. Finally, both sets of features are input into a Gate

Recurrent Unit (GRU) module for RUL prediction. Experimental

results across three tasks demonstrate that our model achieves

excellent generalization capabilities.

Keywords

bearing,RUL prediction,time variant-time invariant,multi-source domain generalization,fast fourier transform

Speaker

正宇邓

Mr Hefei University of Technology

娟徐

Ms Hefei University of Technology

Submission Author

正宇邓 Hefei University of Technology

娟徐 Hefei University of Technology

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Registration Paper Submission

Important Dates

~~15th August~~ ~~2024~~ 31st August 2024- Manuscript Submission

15th September 2024 - Acceptance Notification

1st October 2024 - Camera Ready Submission

1st October 2024 – Early Bird Registration

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https://icsmd2024.aconf.org/