Evidence map›Paper›PMID 34201463›Full record

ArticleEntropy (Basel, Switzerland)2021

Fault Diagnosis of a Wind Turbine Gearbox Based on Improved Variational Mode Algorithm and Information Entropy.

Fan Zhang, Wenlei Sun, Hongwei Wang, Tiantian Xu

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

4 authors.

Fan ZhangSchool of Mechanical Engineering, Xinjiang University, Urumqi 830047, China.
Wenlei SunSchool of Mechanical Engineering, Xinjiang University, Urumqi 830047, China.
Hongwei WangSchool of Mechanical Engineering, Xinjiang University, Urumqi 830047, China.
Tiantian XuSchool of Mechanical Engineering, Xinjiang University, Urumqi 830047, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The working environment of wind turbine gearboxes is complex, complicating the effective monitoring of their running state. In this paper, a new gearbox fault diagnosis method based on improved variational mode decomposition (IVMD), combined with time-shift multi-scale sample entropy (TSMSE) and a sparrow search algorithm-based support vector machine (SSA-SVM), is proposed. Firstly, a novel algorithm, IVMD, is presented for solving the problem where VMD parameters (

Indexed as

fault diagnosissparrow search algorithmsupport vector machinetime-shifting multi-scale sample entropyvariational mode decompositionwind turbine gearbox

Identifiers

PMID34201463
PMCPMC8306640

What OpenQuestion holds

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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.