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Record W2059320422 · doi:10.1109/icphm.2014.7036374

Understanding vibration properties of a planetary gear set for fault detection

2014· article· en· W2059320422 on OpenAlexafffund
Xihui Liang, Ming J. Zuo, Mohammad R. Hoseini

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGear and Bearing Dynamics Analysis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVibrationAcousticsFault (geology)Transmission (telecommunications)Structural engineeringGear trainComputer scienceEngineeringPhysicsSpiral bevel gearGeologyTelecommunications

Abstract

fetched live from OpenAlex

This paper investigates the vibration properties of a planetary gear set. A two-dimensional lumped mass model is developed to simulate the vibration signals of a planetary gear set in the perfect and crack situations. Through dynamic simulation, the vibration signals of each individual component can be simulated, including the vibration signals of the sun gear, each planet gear, and the ring gear. By incorporating the effect of transmission path, resultant vibration signals of the gearbox at the transducer location are obtained. Results show obvious fault symptoms in the signals of an individual component, such as the sun gear. After going through the transmission path, amplitude modulation is shown in the resultant vibration signals. When there is a crack on a sun gear tooth, a large amount of sidebands appears in the vibration spectrum. The locations of these sidebands are investigated and identified, which are helpful for fault detection.

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 score0.748
Threshold uncertainty score0.140

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.045
GPT teacher head0.192
Teacher spread0.147 · 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

Citations15
Published2014
Admission routes2
Has abstractyes

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