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Record W4412109822 · doi:10.1139/tcsme-2024-0138

Inner ring defect frequency deviation of ball bearings induced by slipping effect under starved lubrication

2025· article· en· W4412109822 on OpenAlexvenueno aff
Zhongtang Huo, Jianqi Chen, Lingjuan Hao, Jiansong Gao

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicGear and Bearing Dynamics Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSlippingLubricationBall (mathematics)Roller bearingBall bearingRing (chemistry)Materials scienceBearing (navigation)MechanicsStructural engineeringControl theory (sociology)PhysicsEngineeringMathematicsComputer scienceComposite materialGeometryChemistry

Abstract

fetched live from OpenAlex

The vibration response of locally defective ball bearings is closely related to their lubrication conditions. In this paper, the interaction within the system under starvation conditions is considered, and a dynamic model of lubricant-deficient inner ring defective deep groove ball bearing is established, and the accuracy of the model is verified by experiments. The results show that the slipping behavior of the bearing leads to a deviation between the cage speed and the theoretical value, which modulates the inner ring failure frequency. And the increase in the lack of lubricant significantly increases the friction force, which leads to the increase in the cage rotational speed, and ultimately leads to the decrease in the inner ring failure frequency. At the same time, the increase in rotational speed makes the slipping phenomenon more severe, leading to an increase in the deviation rate of the inner ring failure frequency at the same level of starvation. The results of the study are useful for fault diagnosis and condition monitoring of related equipment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.726
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.193
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicGear and Bearing Dynamics AnalysisFrench-language works237,207