DETECÇÃO DE FALHAS EM MOTORES TRIFÁSICOS COM TECNOLOGIA MCM NA ARCELOR-MITTAL INÓX BRASIL
Bibliographic record
Abstract
PDF | O método de Detecção de Falhas em motores elétricos trifásicos, com tecnologia MCM (Motor Condition Monitor), baseia-se no o conceito de modelamento matemático, para diagnosticar com antecedência as degradações progressivas de natureza elétrica ou mecânica do sistema monitorado. As variações ocorridas no sistema, seja proveniente do processo ou por degradação, são perceptíveis quando analisadas no domínio da freqüência. A detecção de falha progressiva é realizada comparando os sinais de tensões e correntes medidos no processo com os registros do modelo matemático. A eficiência do equipamento foi avaliada utilizando o motor do exaustor de gás da regeneração de ácido. Este trabalho teve como suporte os testes de avaliação realizada pela Gerência de Área de Engenharia de Manutenção (PICE) e a Gerência de Área de Manutenção de Utilidades (PEUM) da ARCELOR- MITTAL Inóx Brasil.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".