Real-Time Multi-Class Disturbance Detection for Φ-OTDR Based on YOLO Algorithm
Abstract
:1. Introduction
2. Principle of Operation
3. Experiment and Result
3.1. Distributed Optical Fiber Sensing System & Data Collection
- (I)
- Calm state
- (II)
- Rigid collisions against the ground
- (III)
- Hitting the protective net
- (IV)
- Shaking the protective net
- (V)
- Cutting the protective net
3.2. Data Pre-Processing
3.3. Comparison between YOLO and Traditional Detection Algorithms
- Locating
- 2.
- Classification
- 3.
- About (I) calm state
3.4. Real-Time Sensing Video Processing
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Type | I | II | III | IV | V |
---|---|---|---|---|---|
Calm State | Rigid Collision | Hit Net | Shake Net | Cut Net | |
Train set size | 560 | 520 | 1352 | 1195 | 424 |
Test set size | 240 | 223 | 580 | 512 | 181 |
Total dataset size | 800 | 743 | 1932 | 1707 | 605 |
Method | Accuracy (%) | Testing Time (sec/img) | Rate (FPS) |
---|---|---|---|
Fast R-CNN | 95.74% | 1.9665 | 0.5085 |
Faster R-CNN | 97.29% | 0.1659 | 6.0277 |
YOLO-based | 96.14% | 0.0438 | 22.8311 |
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Xu, W.; Yu, F.; Liu, S.; Xiao, D.; Hu, J.; Zhao, F.; Lin, W.; Wang, G.; Shen, X.; Wang, W.; et al. Real-Time Multi-Class Disturbance Detection for Φ-OTDR Based on YOLO Algorithm. Sensors 2022, 22, 1994. https://doi.org/10.3390/s22051994
Xu W, Yu F, Liu S, Xiao D, Hu J, Zhao F, Lin W, Wang G, Shen X, Wang W, et al. Real-Time Multi-Class Disturbance Detection for Φ-OTDR Based on YOLO Algorithm. Sensors. 2022; 22(5):1994. https://doi.org/10.3390/s22051994
Chicago/Turabian StyleXu, Weijie, Feihong Yu, Shuaiqi Liu, Dongrui Xiao, Jie Hu, Fang Zhao, Weihao Lin, Guoqing Wang, Xingliang Shen, Weizhi Wang, and et al. 2022. "Real-Time Multi-Class Disturbance Detection for Φ-OTDR Based on YOLO Algorithm" Sensors 22, no. 5: 1994. https://doi.org/10.3390/s22051994