Feature Enhancement Method of Rolling Bearing Based on K-Adaptive VMD and RBF-Fuzzy Entropy.

Jing Jiao, Jianhai Yue, Di Pei

Abstract read

In one paragraph

Article in Entropy (Basel, Switzerland), 2022. 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.

Fuzzy Entropy-Assisted Deconvolution Method and Its Application for Bearing Fault Diagnosis.Entropy (Basel, Switzerland) · 2024
Article
Rolling Bearing Fault Diagnosis Based on WOA-VMD-MPE and MPSO-LSSVM.Entropy (Basel, Switzerland) · 2022
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

3 authors.

Jing JiaoSchool of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijng 100044, China.ORCID 0000-0003-2143-8469

Jianhai YueSchool of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijng 100044, China.

Di PeiSchool of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijng 100044, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The complex and harsh working environment of rolling bearings cause the fault characteristics in vibration signal contaminated by the noise, which make fault diagnosis difficult. In this paper, a feature enhancement method of rolling bearing signal based on variational mode decomposition with

Indexed as

feature enhancingfuzzy entropyrolling element bearingvariational mode decomposition

Identifiers

PMID35205492

DOI10.3390/e24020197

PMCPMC8871395

What OpenQuestion holds

Textmetadata

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.