Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data
Fault detection and diagnosis (FDD) play a vital role in abnormal situation management of chemical industrial processes. Current FDD technologies mostly rely on data-driven solutions by making full use of abundant process data collected by the state-of-the-art distributed process instruments and sen...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
Springer Nature
2025
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| Subjects: | |
| Online Access: | https://eprints.ums.edu.my/id/eprint/45078/1/FULLTEXT.pdf https://eprints.ums.edu.my/id/eprint/45078/ https://doi.org/10.1007/s10489-025-06711-y |
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