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Record W2437604724 · doi:10.1139/tcsme-2014-0005

EFFECT OF INTERNAL POWER-ANGLE ON TURBO-GENERATOR ROTOR VIBRATION CHARACTERISTICS UNDER ECCENTRICITY FAULTS

2014· article· en· W2437604724 on OpenAlexvenueno aff
Shuting Wan, Yuling He, Zhan Changgeng

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicMachine Fault Diagnosis Techniques
Canadian institutionsnot available
FundersFundamental Research Funds for the Central UniversitiesNatural Science Foundation of Hebei ProvinceNational Natural Science Foundation of China
KeywordsMagnetomotive forceTurbo generatorAir gap (plumbing)VibrationRotor (electric)Eccentricity (behavior)PermeanceGenerator (circuit theory)Control theory (sociology)Structural engineeringPermanent magnet synchronous generatorMechanicsEngineeringPower (physics)AcousticsPhysicsComputer scienceMechanical engineeringElectromagnetic coilElectrical engineeringMaterials scienceMagnet

Abstract

fetched live from OpenAlex

This paper investigates the effect of the turbo-generator internal power-angle on the rotor radial vibration characteristics under air gap eccentricity faults. Firstly the air gap magnetomotive force, the magnetic permeance and the magnetic flux density of the eccentricity faults is deduced, and the formula of the magnetic pull per unit area is obtained. Then the restrictive factors of the magnetomotive force and the internal powerangle are analyzed. The unbalanced magnetic pull (UMP) that acts on the rotor is further deduced, and the rotor vibration characteristics are given. Finally the experiments are taken on a SDF-9 non-salient fault simulating generator to verify the theoretical results. The investigation results of this paper will be beneficial to air gap eccentricity faults diagnosis of turbo-generator.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.736
Threshold uncertainty score0.672

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 head0.004
GPT teacher head0.216
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

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

Citations2
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicMachine Fault Diagnosis TechniquesFrench-language works237,207