MétaCan
Menu
Back to cohort

Field Validation of a Local, Traveling-Wave, Fault Detection Method for DC Microgrids

2023· article· en· W4389077653 on OpenAlexaff
Javier Hernández-Alvídrez, Andrew R. R. Dow, Miguel Jimenez Aparicio, Matthew J. Reno, Daniel J. Bauer, Daniel Ruiz

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsEmera (Canada)
FundersU.S. Department of Energy
KeywordsDigital signal processingEmulationOscilloscopeFault (geology)Digital signal processorVoltageComputer scienceSIGNAL (programming language)Electronic engineeringFilter (signal processing)Fault detection and isolationElectrical engineeringEngineeringComputer hardware

Abstract

fetched live from OpenAlex

This paper proposes and validates a near realtime fault detection method using Traveling Waves (TWs) for DC microgrids. The method can be executed on low-cost embedded devices. Local positive pole voltage measurements are obtained at a high-sampling rate of 1 MHz, and a second-order high-pass filter is used to detect high-frequency transients on such time-series. A fault emulation hardware is assembled on a real DC microgrid to validate the performance of the method. A Texas Instrument Digital Signal Processor (DSP) device is mounted onto a custom signal-conditioning board. When a TW is detected, the DSP is capable of recording positive and negative pole voltages and positive pole current around the TW arrival time. Results show that the DSP's recording capabilities are similar to commercial oscilloscopes. This method can provide an accurate TW detection on DC microgrids in less than 15 microseconds.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.895
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

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

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 head0.020
GPT teacher head0.279
Teacher spread0.259 · 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 teacher head, 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicPower Systems Fault DetectionFrench-language works237,207