High Accuracy Vibration Sensing by using Random Interval Forest Classifier Based Distributed Fiber Sensing
We present a novel machine-learning technique for vibration detection, called random interval forest classifier (RIFC), using a single Mach-Zehnder interferometer based on single-mode fiber. Our method achieved 98% accuracy with very low complexity.
Authors
- Brian Pamukti (ORCID: https://orcid.org/0000-0003-3824-9306)
- Totok Soehartanto (ORCID: https://orcid.org/0000-0001-8459-2709)
- Agus Muhamad Hatta (ORCID: https://orcid.org/0000-0001-5176-5933)
- Shien‐Kuei Liaw (ORCID: https://orcid.org/0000-0001-6225-9382)
- Zi Wang (ORCID: https://orcid.org/0000-0002-5081-661X)
- Yamei Yang
Institutions
- National Taiwan University of Science and Technology (TW)
- Sepuluh Nopember Institute of Technology (ID)
- Industrial Technology Research Institute (TW)
Publication Details
- Published
- 2024-08-04
- DOI
- https://doi.org/10.1109/cleo-pr60912.2024.10676897
- Primary Topic
- Advanced Fiber Optic Sensors
- Type
- article
- Field-Weighted Citation Impact
- 0.00