Evidence map›Paper›PMID 34577379›Full record

ArticleSensors (Basel, Switzerland)2021

An IoT-Based System for Monitoring the Health of Guyed Towers in Overhead Power Lines.

Claudio Ferreira Dias, Juliane Regina de Oliveira, Lucas D de Mendonça, Larissa M de Almeida, Eduardo R de Lima, Lucas Wanner

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

6 authors.

Claudio Ferreira DiasInstituto de Pesquisas Eldorado, Campinas 13083-898, Brazil.ORCID 0000-0003-0490-3330
Juliane Regina de OliveiraInstitute of Computing, University of Campinas, Campinas 13083-859, Brazil.ORCID 0000-0002-0630-3083
Lucas D de MendonçaInstituto de Pesquisas Eldorado, Campinas 13083-898, Brazil.
Larissa M de AlmeidaTaesa S.A., Rio de Janiero 20010-010, Brazil.
Eduardo R de LimaInstituto de Pesquisas Eldorado, Campinas 13083-898, Brazil.ORCID 0000-0003-4268-9726
Lucas WannerInstitute of Computing, University of Campinas, Campinas 13083-859, Brazil.ORCID 0000-0002-5564-698X

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 13239/2017-7TAESA S.A. PD-07130-0047
6 · The paper itself

Abstract

The collapse of overhead power line guyed towers is one of the leading causes of power grid failures, subjecting electricity companies to pay considerable, high-value fines. In this way, the current work proposes a novel and complete framework for the remote monitoring of mechanical stresses in guyed towers. The framework method comprises a mesh network for data forwarding and neural networks to improve the performance of Low-Power and Lossy Networks. The method also considers the use of multiple sensors in the sensor fusion technique. As a result, the risk of collapse of guyed cable towers reduces, due to the remote monitoring and preventive actions promoted by the framework. Furthermore, the proposed method uses multiple input variable fusions, such as accelerometers and tension sensors, to estimate the tower's displacement. These estimations help address the structural health of the tower against failures (i.e., loosening of the stay cables, displacement, and vibrations) that can cause catastrophic events, such as tower collapse or even cable rupture.

Indexed as

Neural Networks, Computerguyed transmission linesInternet of Thingsremote monitoringtower collapse

Identifiers

PMID34577379
PMCPMC8469143

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.