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Record W3004569350 · doi:10.1088/1361-665x/ab72e6

Acoustic guided wave detection of grounding rod corrosion: equivalent circuit model and implementation

2020· article· en· W3004569350 on OpenAlexaff
Nicholas M. Durham, Junhui Zhao, Gregory Bridges, D. J. Thomson

Bibliographic record

VenueSmart Materials and Structures · 2020
Typearticle
Languageen
FieldEngineering
TopicUltrasonics and Acoustic Wave Propagation
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsRodAcousticsTransducerCorrosionGroundGuided wave testingMaterials sciencePulse (music)EngineeringStructural engineeringElectrical engineeringVoltagePhysicsComposite material

Abstract

fetched live from OpenAlex

Abstract Acoustic pulse-echo systems, are effective for corrosion damage detection in buried individual ground rods without any need for excavation. In electric power distribution systems there are large numbers buried ground rods are used in substations to form a grounding networks that is critical for the protection of equipment and personnel working in the vicinity of the substation. Over time, these grounding rods will corrode and cease to provide adequate protection. In this work, we present an equivalent circuit model (ECM) for acoustic pulse-echo corrosion detection systems. The circuit model was used to develop a transducer configuration that effectively launches longitudinal acoustic waves that can accurately detect position and damage severity. We show that our model correctly predicts the temporal response from both undamaged rods and rods with machined simulated corrosion pits. The circuit model also accounts for loss, and the results show strong agreement with simulated soil-loss in laboratory experiments. Evidence of wave mode conversion is found in experimental data that is not captured by the model. Preliminary field measurements of copper-clad steel grounding rods are presented that show strong similarities to modeled results. This ECM is a promising basis for further development of pulse-echo systems for corrosion detection and may be useful for future tomographic analysis of field measurements.

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: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.376

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 head0.029
GPT teacher head0.241
Teacher spread0.212 · 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

Citations14
Published2020
Admission routes1
Has abstractyes

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