Real-Time Diagnosis for Open-Circuited and Unbalance Faults in Electronic Converters Connected to Residential Wind Systems
Bibliographic record
Abstract
This paper presents real-time diagnosis for open-circuited (O-C) and unbalance faults in power electronic converters (PECs) connected to residential small wind systems grid-tied. The spectrum analysis along with the dc components of the voltage and current measurements available in the converter is utilized for the O-C fault detection, classification and localization of the power switching devices in the PEC, as well as the identification of the unbalance input voltage to the converter. The proposed methodologies in this paper require much fewer inputs compared to the previous researches; therefore, they avoid any additional sensors or hardware which include further costs and expenses on such systems. The experimental evaluations for the proposed algorithms are provided and demonstrate the effectiveness and the robustness of the proposed diagnostic algorithms in this paper. The PEC under study consists of three main subsystems: uncontrolled three-phase rectifier, boost chopper, and single-phase inverter.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".