Evidence map›Paper›PMID 40096300›Full record

ArticleSensors (Basel, Switzerland)2025

High-Precision, Self-Powered Current Online Monitoring System Based on TMR Sensors Array for Distribution Networks.

Zhengang An, Lei Zhang, Zhi Wang, Yanyun Fan, Zhiwei Zu, Zhengzhe Li, Dachao Li

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Zhengang AnState Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China.
Lei ZhangState Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China.ORCID 0000-0002-9626-4574
Zhi WangState Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China.
Yanyun FanState Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China.
Zhiwei ZuState Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China.
Zhengzhe LiState Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China.
Dachao LiState Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China.

Funding

National Natural Science Foundation of China 62105238
6 · The paper itself

Abstract

Establishing a maintenance-free current sensing network across the entire power grid to facilitate wide-area online monitoring is crucial for realizing a smart grid. However, distribution networks (DNs) frequently lack effective real-time current monitoring owing to the complexity of load types, extensive line distribution, and numerous branches. In this study, we propose a high-precision, self-powered online current monitoring system that integrates a TMR sensors array module, a main control module, a current transformer (CT) power harvesting module, and current online monitoring software. The TMR sensors array module boasts a measurement range of 0-300 A and a high sensitivity of 25.38 mV/A. To address wire eccentricity errors in array sensors, we develop a neural network-based correction algorithm, which identifies wire positions and applies correction coefficients, achieving high accuracy with an average error of 1.23%. Current data are wirelessly transmitted to software terminals via 4G communication for remote monitoring. Furthermore, the CT power harvesting module converts magnetic energy from the power grid into electrical energy, ensuring that the system is self-powered. Validation through continuous 24-h monitoring of DNs demonstrates the system's high precision and stability. This work presents an effective solution for high-accuracy online current monitoring in DNs.

Indexed as

current online monitoring systemcurrent sensorpower distribution networkself-poweredTMR sensor

Identifiers

PMID40096300
PMCPMC11902725

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.