Remaining useful life prediction using an integrated Laplacian-LSTM network on machinery components
Accurate remaining useful life (RUL) analysis of a machinery system is of great importance. Such systems work in long-term operations in which unexpected failures often occur. Due to the rapid development of computer technology, the deep learning model has supplanted physical-based RUL analysis. The...
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| Main Authors: | , |
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| Format: | Article |
| Published: |
Elsevier Ltd
2021
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/96888/ http://dx.doi.org/10.1016/j.asoc.2021.107817 |
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| Institution: | Universiti Teknologi Malaysia |