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Record W2801622787 · doi:10.1139/tcsme-2005-0027

A TEST RIG FOR EXPERIMENTATION ON FAULT TOLERANT CONTROL AND CONDITION MONITORING ALGORITHMS IN FLUID POWER SYSTEMS: FROM DESIGN THROUGH IMPLEMENTATION

2005· article· en· W2801622787 on OpenAlexaffvenueabout
Nariman Sepehri, Mark Karpenko, Liang An, Suha Karam

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2005
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsFluid powerBenchmark (surveying)AerospaceFault (geology)ActuatorPower (physics)EngineeringComputer scienceControl engineeringReliability engineeringMechanical engineeringAerospace engineering

Abstract

fetched live from OpenAlex

This paper reports the relevant aspects of a novel experimental test facility for research on fault tolerant control design and condition monitoring of fluid power systems recently constructed at the University of Manitoba. Common faults and their effects on the operation of valve controlled hydraulic actuators, such as those found in aerospace applications, are summarized first. The manuscript then presents the main features of the test rig and the modifications made to simulate various faults. The design also incorporates techniques to easily simulate load conditions from viscous forces to complex dynamic loads. The significance of the test rig in the development of advanced condition monitoring and fault tolerant control strategies is also illustrated by the presentation of the results of some recent research work conducted using the test facility. By sharing their experience with other investigators in this active area of fluid power research, the authors hope to establish a national benchmark test facility for the objective evaluation of state-of-the-art monitoring and control strategies for fluid power systems.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.961
Threshold uncertainty score0.813

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 head0.017
GPT teacher head0.255
Teacher spread0.237 · 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 designSimulation or modeling
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

Citations10
Published2005
Admission routes3
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicHydraulic and Pneumatic SystemsFrench-language works237,207