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Record W2059018729 · doi:10.1109/eic.2009.5166352

Innovative web system for condition-based maintenance of generators

2009· article· en· W2059018729 on OpenAlex
C. Hudon, M. Bélec, D.N. Nguyen

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsComputer scienceGenerator (circuit theory)Interface (matter)Reliability engineeringThe InternetUser interfaceIndex (typography)Simple (philosophy)Data miningReal-time computingEngineeringOperating system

Abstract

fetched live from OpenAlex

A novel integrated diagnostic system has been developed at IREQ, the research institute of Hydro-Quebec, over the last eight years. The goal of this project was to build an integrated methodology for generator diagnostics using the results from on-site measurement tools, which would help the utility to make the transition from time-based maintenance to condition-based maintenance. The system makes use of information technology (Internet) to provide a new, modern and efficient way to produce a continuous classification of the condition of all generators of a fleet along with individual diagnostics for any unit at any time. The system computes actual measurements provided by plant personnel who transfer data files to a centralized server. The application calculates simple condition indexes from each of six on-line/off-line diagnostic tools and from visual inspections, and aggregates the results into a comprehensive global diagnostic for the selected generator. Plant and generator selection is done via a user-friendly interface displaying a simple rating of the results for every tool. The algorithm underlying the system generates a global diagnostic for any combination of tools, regardless of their number and selection. However, the level of confidence of the diagnostic will increase with the number of tools used for the diagnostic. In addition to the simplified integrated condition index values of all generators and the individual index for each tool, specialists can access and display the complete data for every measurement series. Each tool, some commercial, others developed at Hydro-Quebec, was selected based on its ability to characterize specific complementary aspects of the generator. Since the system was developed with an expandable modular approach, it will be possible in the future to add new diagnostic tools, not yet considered in the current version, without affecting the logic of the system. Hydro-Quebec has recently implemented this new system and is already noting improvement in maintenance practices. The ready availability of centralized, simplified information makes it possible for generator specialists and managers alike to assess the condition of any generator in a few minutes. Thanks to this new diagnostic system, technical and management staff can now work together with common information and in real time to optimize maintenance intervention on generators showing degradation. Thus, it is possible to plan any corrective action more effectively or request additional testing when doubts remain about active degradation mechanisms. At the same time, efforts in diagnosis and maintenance could be optimized by reducing the number of measurement campaigns for the vast majority of generators that are in good condition as revealed by their condition indexes.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.529
Threshold uncertainty score0.196

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 head0.007
GPT teacher head0.220
Teacher spread0.213 · 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

Quick stats

Citations11
Published2009
Admission routes2
Has abstractyes

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