Raw Data Library
About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide
Green Science
​
​
EN
Kurumsal BaşvuruSign inGet started
​
​

About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User GuideGreen Science

Language

Kurumsal Başvuru

Sign inGet started
RDL logo

Verified research datasets. Instant access. Built for collaboration.

Navigation

About

Aims and Scope

Advisory Board Members

More

Who We Are?

Contact

Add Raw Data

User Guide

Legal

Privacy Policy

Terms of Service

Support

Got an issue? Email us directly.

Email: info@rawdatalibrary.netOpen Mail App
​
​

© 2026 Raw Data Library. All rights reserved.
PrivacyTermsContact
  1. Raw Data Library
  2. /
  3. Publications
  4. /
  5. Artificial-Neural-Network-Assisted Distributed Directional Optical Fiber Torsion Sensor With the SSAF-Based Sagnac Interferometer

Verified authors • Institutional access • DOI aware
50,000+ researchers120,000+ datasets90% satisfaction
Article
en
2024

Artificial-Neural-Network-Assisted Distributed Directional Optical Fiber Torsion Sensor With the SSAF-Based Sagnac Interferometer

0 Datasets

0 Files

en
2024
Vol 42 (16)
Vol. 42
DOI: 10.1109/jlt.2024.3397798

Get instant academic access to this publication’s datasets.

Create free accountHow it works

Frequently asked questions

Is access really free for academics and students?

Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.

How is my data protected?

Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.

Can I request additional materials?

Yes, message the author after sign-up to request supplementary files or replication code.

Advance your research today

Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.

Get free academic accessLearn more
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaboration
Access Research Data

Join our academic network to download verified datasets and collaborate with researchers worldwide.

Get Free Access
Institutional SSO
Secure
This PDF is not available in different languages.
No localized PDFs are currently available.
Paul Kim Ho Chu
Paul Kim Ho Chu

Institution not specified

Verified
Jiaqi Cao
Biao Wang
Bingsen Huang
+3 more

Abstract

A distributed optical fiber torsion sensor assisted by an artificial neural network (ANN) is designed based on the single stress-applying fiber (SSAF)-based Sagnac interferometer and demonstrated experimentally. A theoretical model is established to describe the piecewise torsion of the high birefringent fiber in the Sagnac loop, and the ANN algorithm is employed to demodulate the distributed torsion signals. The experimental results demonstrate the ability to simultaneously measure the torsion position and torsion angle when only one position along the fiber is subjected to torsion. The average R 2 and MAE of three predictions of the single torsion position are 0.984 and 0.55 cm, and those of the torsion angle are 0.998 and 1.98° for torsion angles from -120° to +120°. When two positions along the fiber are subjected to torsion, the R 2 and MAE of the torsion angle are 0.96/11.31° and 0.99/2.17° for torsion angles between -120° and +120°. The sensing system is demonstrated to demodulate the torsion of the wrist joint and elbow joint of the human arm. This promising strategy not only achieves the highest torsion position resolution and shortest response time, but also can be used to perform distributed torsion measurement and torsion direction recognition at the same time in addition to measuring the torsion at multiple positions, thereby showing great potential in applications such as robotic arms.

How to cite this publication

Jiaqi Cao, Biao Wang, Bingsen Huang, Shuqin Lou, Zhufeng Sheng, Paul Kim Ho Chu (2024). Artificial-Neural-Network-Assisted Distributed Directional Optical Fiber Torsion Sensor With the SSAF-Based Sagnac Interferometer. , 42(16), DOI: https://doi.org/10.1109/jlt.2024.3397798.

Related publications

Why join Raw Data Library?

Quality

Datasets shared by verified academics with rich metadata and previews.

Control

Authors choose access levels; downloads are logged for transparency.

Free for Academia

Students and faculty get instant access after verification.

Publication Details

Type

Article

Year

2024

Authors

6

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1109/jlt.2024.3397798

Join Research Community

Access datasets from 50,000+ researchers worldwide with institutional verification.

Get Free Access