Remaining useful life prediction for equipment based on RF-BiLSTM
The prediction technology of remaining useful life has received a lot attention to ensure the reliability and stability of complex mechanical equipment. Due to the large-scale, non-linear, and high-dimensional characteristics of monitoring data, machine learning does not need an exact physical model...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2022-11-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0125885 |