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Record W4321609132 · doi:10.1109/tpel.2023.3245052

Accurate SM Disturbance Observer-Based Demagnetization Fault Diagnosis With Parameter Mismatch Impacts Eliminated for IPM Motors

2023· article· en· W4321609132 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

VenueIEEE Transactions on Power Electronics · 2023
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsControl theory (sociology)StatorFlux linkageDisturbance (geology)Demagnetizing fieldFault (geology)Observer (physics)EngineeringComputer scienceInduction motorDirect torque controlVoltagePhysicsMagnetic fieldGeologyArtificial intelligence

Abstract

fetched live from OpenAlex

This letter proposes a novel sliding mode (SM) disturbance observer-based technique to diagnose demagnetization fault of interior permanent magnet (IPM) motors with stator parameter mismatch impacts eliminated. First, the IPM motor model incorporating the disturbances caused by the PM demagnetization and stator parameter mismatch is established. Then, an SM disturbance observer is constructed to identify the overall disturbance caused by all parameters, with its stability discussed by using the Lyapunov function. Third, a current-analysis-based method is developed to extract the disturbance only caused by flux linkage mismatch from the overall disturbance. Third, the extracted disturbance is adopted to calculate the real flux linkage, achieving demagnetization fault judgment and demagnetization degree calculation. Finally, experiment is conducted on two IPM motors to validate the proposed flux linkage estimation and fault diagnosis methods.

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 categoriesMeta-epidemiology (narrow)
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 score0.720
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.229
Teacher spread0.216 · 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