Floating Neutral Detection Using Actual Generation of Form 2S Meters
Bibliographic record
Abstract
In the low-voltage distribution system of the USA, Canada and some countries of Central and South America, the most used configuration is the single-phase three-wire system (120 V/240 V) also known as the split-phase distribution system. When the neutral wire of the distribution system gets damaged or broken the current returns through the ground and a floating neutral condition arises. Service to the house continues without interruptions because no high over-currents come up. If the return path impedance is high enough, the equally balanced voltage system gets shifted, going out of boundaries and causing malfunctions in the appliances or even fire. A new classification-based detector is proposed to detect this condition, which only needs current measurements that the actual generation of form 2S meter gathers. Moreover, due to the simplicity of the algorithm, it can be embedded in the current generation of meters, which represents great potential of the detector. To that end, the low-voltage distribution system is modelled using a real database and some assumptions are made. The proposed novel detector approach shows zero false alarms in the houses tested and a detection time that allows the fault to be detected before significant damage occurs to the house.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".