Intensity and Wavelength-Division Multiplexing Fiber Sensor Interrogation Using a Combination of Autoencoder Pre-Trained Convolution Neural Network and Differential Evolution Algorithm
This paper proposes a new fiber Bragg grating central wavelength interrogation system by combining evolutionary algorithm and machine learning techniques integrated with an unsupervised autoencoder (AE) pre-training strategy. The proposed unsupervised AE pre-training convolution neural network (CNN)...
Saved in:
| Main Authors: | Po-Han Chiu, Yu-Shen Lin, Yibeltal Chanie Manie, Jyun-Wei Li, Ja-Hon Lin, Peng-Chun Peng |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
|
| Series: | IEEE Photonics Journal |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9319234/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Long-Term Wavelength Stability of Large Type II FBG Arrays in Different Silica-Based Fibers at High Temperature
by: Robert B. Walker, et al.
Published: (2025-03-01) -
FBG Interrogator Using a Dispersive Waveguide Chip and a CMOS Camera
by: Zhenming Ding, et al.
Published: (2024-09-01) -
A Passive Ladder-Shaped FBG Sensor Network with Fault Detection Using Time- and Wavelength-Division Multiplexing
by: Keiji Kuroda
Published: (2025-07-01) -
Tunable Multimode Fiber Based Filter and Its Application in Cost-Effective Interrogation of Fiber-Optic Temperature Sensors
by: Li Wei, et al.
Published: (2017-01-01) -
Phase-Shifted Bragg Grating based on Silicon-on-Insulator Nanowire
by: QIN Zhibin, et al.
Published: (2024-12-01)