MétaCan
Menu
Back to cohort
Record W4206377503 · doi:10.1109/ias48185.2021.9677101

Survivability-Based Protection for 3ϕ Induction Motor Drives

2021· article· en· W4206377503 on OpenAlexaff
S. A. Saleh, E. Ozkop, Mustafa Şinasi Ayas, Kashem M. Muttaqi, Babak Nahid‐Mobarakeh

Bibliographic record

Venue2021 IEEE Industry Applications Society Annual Meeting (IAS) · 2021
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsMcMaster UniversityUniversity of New Brunswick
Fundersnot available
KeywordsSurvivabilityReliability engineeringComputer scienceInduction motorEngineeringElectrical engineeringVoltage

Abstract

fetched live from OpenAlex

This paper develops a survivability-based protection for three phase induction motor drive (3ϕ IMDs) systems against severe dynamic events. The developed protection is based on defining a survivability index ΓIMD, which is formulated in terms of the change in power created by a dynamic event experienced by a 3ϕ IMD. The determination of ΓIMDprovides an accurate tool to detect, identify, and respond to unsurvivable dynamic events. The efficacy and validity of the survivability-based protection for 3ϕ IMDs are verified through simulation and experimental tests. These tests are conducted for 10hp 3ϕ IMD under various types of dynamic events. Test results demonstrate the effectiveness of the survivability-based protection in responding to unsurvivable dynamic events to prevent damage to different components in a 3ϕ IMD.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.246
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

Same venue2021 IEEE Industry Applications Society Annual Meeting (IAS)Same topicMultilevel Inverters and ConvertersFrench-language works237,207