RDL logo
About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide
​
​
Sign inGet started
​
​

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

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?

Add Raw Data

User Guide

Legal

Privacy Policy

Terms of Service

Support

Got an issue? Email us directly.

Email: info@rawdatalibrary.netOpen Mail App
​
​

© 2025 Raw Data Library. All rights reserved.
PrivacyTerms
  1. Raw Data Library
  2. /
  3. Publications
  4. /
  5. High‐Accuracy Liquid Flow Monitoring via Triboelectric Nanogenerator Combined with Bionic Design and Common‐Mode Interference Suppression

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

High‐Accuracy Liquid Flow Monitoring via Triboelectric Nanogenerator Combined with Bionic Design and Common‐Mode Interference Suppression

0 Datasets

0 Files

en
2024
DOI: 10.1002/adfm.202415534

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.
Zhong Lin Wang
Zhong Lin Wang

Beijing Institute of Technology

Verified
Siyang He
Yang Zheng
Jianlong Wang
+7 more

Abstract

Abstract In the development of smart cities, accurate liquid flow monitoring is essential for the efficient operation of water supply systems. Current flow sensors often face limitations in sensitivity and environmental adaptability, affecting measurement accuracy, and restricting their application in smart city infrastructure. To address these challenges, this study proposes a high‐accuracy flow monitoring method. Specifically, by combining the bionic design with advanced signal processing techniques, the sensitivity and anti‐interference ability are improved, respectively, to enhance the measurement accuracy. Based on this method, a self‐powered flow sensor (SPFS) is developed using noncontact triboelectric nanogenerators (NC‐TENGs) as the sensing unit. The SPFS achieves a sensitivity of 2.07 Hz L −1 min −1 and improves the signal‐to‐noise ratio by more than 13 times over the initial sensing signal. In addition, an intelligent system is developed to accurately measure water resources. The maximum flow rate error rate is less than 0.97% compared to commercial flow sensors. The SPFS demonstrates higher sensitivity and accuracy compared to the existing TENG flow sensors. This study addresses the limitations of existing flow sensors and pioneers a novel solution for enhanced water resource management in smart cities.

How to cite this publication

Siyang He, Yang Zheng, Jianlong Wang, Xinxian Wang, Jiacheng Zhang, Xin Guo, Hengyu Li, Tinghai Cheng, Zhong Lin Wang, Xiaojun Cheng (2024). High‐Accuracy Liquid Flow Monitoring via Triboelectric Nanogenerator Combined with Bionic Design and Common‐Mode Interference Suppression. , DOI: https://doi.org/10.1002/adfm.202415534.

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

10

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/adfm.202415534

Join Research Community

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

Get Free Access