Evidence map›Paper›PMID 41374713›Full record

ArticleSensors (Basel, Switzerland)2025

Bearing Fault Diagnosis via FMD with Parameters Optimized by an Improved Crested Porcupine Optimizer.

Ping Pan, Hao Liu, Bing Lei, Xiaohong Tang

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Ping PanSchool of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China.
Hao LiuSchool of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China.
Bing LeiSchool of Intelligent Technology, Jiangxi Open University, Nanchang 330046, China.
Xiaohong TangSchool of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China.ORCID 0009-0003-3834-0377

Funding

Science and Technology Project of Jiangxi Provincial Department of Education GJJ2200626Science and Technology Project of Jiangxi Provincial Department of Education GJJ2207604Science and Technology Project of Jiangxi Provincial Department of Transportation 2023Z0003
6 · The paper itself

Abstract

Feature Mode Decomposition (FMD) can effectively extract bearing fault features even in the case of strong interference noise by means of adaptive finite impulse response filter banks along with correlated kurtosis. Nevertheless, the filter length

Indexed as

fault diagnosisfeature extractionfeature mode decompositionimproved crested porcupine optimizerrolling bearing

Identifiers

PMID41374713
PMCPMC12694669

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.