A Comprehensive Evaluation of Thermal Overload Protection Systems: Experimental Validation and Predictive Modeling Under Cold and Hot Curve Conditions
Bibliographic record
Abstract
Thermal overload protection is a fundamental function for ensuring the safety and reliability of electrical equipment under sustained overcurrent conditions.This study presents experimental validation and predictive modeling of the SEPAM 1000+ T20 thermal overload relay under cold and hot curve operating conditions defined by IEC 60255-149.A first-order thermal model was applied to determine alarm (ES1) and trip (ES2) thresholds, followed by laboratory testing to measure actual alarm and tripping times across multiple overload levels.The results showed strong agreement with theoretical predictions, with deviations consistently below 5%.A predictive model based on simple linear regression further confirmed this consistency, yielding a slope coefficient of 1.0039 and R² exceeding 0.98.These findings validate that the SEPAM 1000+ T20 relay operates within IEC performance limits, while demonstrating the importance of considering both cold and hot curve characteristics when configuring protection systems.The proposed predictive model provides a reliable framework for optimizing relay settings, minimizing nuisance tripping, and improving the reliability of industrial thermal protection schemes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".