Nonlinear error compensation for microfiber knot current sensors based on artificial neural network

Chen, Ming‐Hui; Geng, Shihang; Zheng, Fangzhu; He, Yingdong; Han, Jinjin; Dai, Hao; Wu, Zhijun; Pu, Jixiong; Zhang, Xining; Lin, Zhihong

doi:10.1016/j.yofte.2023.103459

Optical Fiber Technology

2023

DOI: 10.1016/j.yofte.2023.103459

|View full text |Cite

Nonlinear error compensation for microfiber knot current sensors based on artificial neural network

Ming‐Hui Chen

Shihang Geng

Fangzhu Zheng

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

2025

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Microfiber Knot Resonators: Structure, Spectral Properties, and Sensing Applications

Zhang,

Gao,

Xia

et al. 2023

Laser & Photonics Reviews

View full text Add to dashboard Cite

In recent years, compact micro‐/nanofiber sensors with fast response and high resolution have become a hot field in sensing and nanotechnology. In addition to the unique properties of microfibers such as strong evanescent field, low optical loss, and easy integration, microfiber knot resonators further improve the sensing capability due to their resonance properties. The potential high‐quality factor allows higher sensing sensitivity and resolution, which is very attractive for optical sensing at the micro‐/nano scale. More application potential can be effectively stimulated by improving the structure shape or principle or combining with functional sensitive materials. This paper first introduces the preparation process and spectral characteristics of conventional microfiber knots and then focuses on three new types of devices for enhancing the sensing performance, namely material‐coated, shape‐improved, and principle‐extended, and briefly analyzes their spectral properties. In addition, the research progress and applications of these sensors are summarized. Finally, the existing problems in this field are analyzed, and the directions for further development are discussed and prospected.

show abstract

Microfiber Knot Resonators: Structure, Spectral Properties, and Sensing Applications

Zhang,

Gao,

Xia

et al. 2023

Laser & Photonics Reviews

View full text Add to dashboard Cite

show abstract

Multi-information perception of aqueous solutions by deep learning-assisted fluorescent microwire sensors

Zheng,

Ouyang,

Wang

et al. 2025

Optics & Laser Technology

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Nonlinear error compensation for microfiber knot current sensors based on artificial neural network

Cited by 2 publications

References 35 publications

Microfiber Knot Resonators: Structure, Spectral Properties, and Sensing Applications

Microfiber Knot Resonators: Structure, Spectral Properties, and Sensing Applications

Multi-information perception of aqueous solutions by deep learning-assisted fluorescent microwire sensors

Contact Info

Product

Resources

About