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Record W1985997835 · doi:10.1115/1.4004683

Time-Varying Meshing Stiffness Calculation and Vibration Analysis for a 16DOF Dynamic Model With Linear Crack Growth in a Pinion

2011· article· en· W1985997835 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of vibration and acoustics · 2011
Typearticle
Languageen
FieldEngineering
TopicGear and Bearing Dynamics Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPinionStructural engineeringVibrationStiffnessAutoregressive modelEngineeringAcousticsMathematicsPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

A modified mathematical model for simulating gear crack from root with linear growth path in a pinion is developed, in which an improved potential energy method is used to calculate the time-varying meshing stiffnesses of the meshing gear pair while we also take the deformation of gear-body into consideration. The formulas for the meshing stiffness are deduced when the crack grows as the linear growth path in the pinion. A 16DOF dynamic model of a one-stage spur gear system is used to study the response from the system considering time-varying meshing stiffnesses and different levels of crack growing in the pinion. As vibration signals induced by the tooth crack are buried in normal vibration signals which are induced by the normal gear pair in meshing at the early stage of crack growth, the algorithm combined autoregressive modeling method and demodulation method is proposed to process the signals to investigate the response characteristics as the crack grows, and the comparison of the relationship between indicators and the crack levels from different simulation methods are given.

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.

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 score0.526
Threshold uncertainty score0.327

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 head0.013
GPT teacher head0.226
Teacher spread0.212 · 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