Compound fault diagnosis of rolling bearings using adaptive spiral flying sparrow search algorithm-variational mode decomposition-sample entropy (ASFSSA-VMD-SampEn) with a hybrid particle swarm optimization-convolutional neural network (HPSO-CNN).
- DOI
- 10.1063/5.0323922
- Published
- 2026 Sep 1
- Container
- The Review of scientific instruments
- Publisher
- Not recorded
- Open access
- no
Credibility signals
limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.1063/5.0323922,
title = {Compound fault diagnosis of rolling bearings using adaptive spiral flying sparrow search algorithm-variational mode decomposition-sample entropy (ASFSSA-VMD-SampEn) with a hybrid particle swarm optimization-convolutional neural network (HPSO-CNN).},
author = {Wei T and Bie F and Lyu F and Li Q and Chao Z and Dong H and Miao X},
year = {2026},
journal = {The Review of scientific instruments},
doi = {10.1063/5.0323922},
url = {https://doi.org/10.1063/5.0323922}
}RIS
TY - JOUR TI - Compound fault diagnosis of rolling bearings using adaptive spiral flying sparrow search algorithm-variational mode decomposition-sample entropy (ASFSSA-VMD-SampEn) with a hybrid particle swarm optimization-convolutional neural network (HPSO-CNN). AU - Wei T AU - Bie F AU - Lyu F AU - Li Q AU - Chao Z AU - Dong H AU - Miao X PY - 2026 JO - The Review of scientific instruments DO - 10.1063/5.0323922 UR - https://doi.org/10.1063/5.0323922 ER -
APA
T, W., F, B., F, L., Q, L., Z, C., H, D., & X, M. (2026). Compound fault diagnosis of rolling bearings using adaptive spiral flying sparrow search algorithm-variational mode decomposition-sample entropy (ASFSSA-VMD-SampEn) with a hybrid particle swarm optimization-convolutional neural network (HPSO-CNN).. The Review of scientific instruments. https://doi.org/10.1063/5.0323922
Source records
- pubmed · retrieved 2026-09-25T19:17:48.657Z
- europe-pmc · retrieved 2026-09-25T19:17:48.676Z