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Record W2472034378 · doi:10.1016/j.ifacol.2015.09.716

Active Fault Tolerant Control in a Wind Farm with Decreased Power Generation Due to Blade Erosion/Debris Build-Up

2015· article· en· W2472034378 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIFAC-PapersOnLine · 2015
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsConcordia University
Fundersnot available
KeywordsOffshore wind powerWind powerTurbineReliability (semiconductor)Marine engineeringFault (geology)Benchmark (surveying)Active faultScheme (mathematics)EngineeringDebrisBlade (archaeology)Reliability engineeringPower (physics)MeteorologyStructural engineeringGeologySeismologyElectrical engineeringAerospace engineering

Abstract

fetched live from OpenAlex

Given the importance of reliability issue in wind farms, the current paper presents the design and development of a novel active fault-tolerant control scheme for an offshore wind farm against decreased power generation caused by turbine blade erosion and debris build-up on the blades over time. The proposed scheme employs a model-based fault detection and diagnosis approach to provide accurate and timely diagnosis information to be used in an appropriate automatic signal correction algorithm. The effectiveness of the proposed scheme is evaluated by simulations on an advanced offshore wind farm benchmark model in the presence of wind turbulences, measurement noises and load variations.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.901

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 head0.015
GPT teacher head0.234
Teacher spread0.219 · 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