MétaCan
Menu
Back to cohort
Record W2073254725 · doi:10.1109/aero.2007.352880

Seeded Failure Testing and Analysis of an Electro-Mechanical Actuator

2007· article· en· W2073254725 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMechanical Failure Analysis and Simulation
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsActuatorReliability engineeringComputer scienceEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

An accelerated wear test program for an electromechanical actuator (EMA) was funded and conducted by Parker Aerospace and Lockheed Martin Aeronautics Company. Testing was performed at Dynamic Controls, Inc. The objective of the program was to identify failure pre-cursors that exhibited repeatable trends, and could be used to construct a remaining useful life algorithm with an identifiable confidence level. Selected mechanical components of the actuator were seeded with an abrasive contaminant to achieve accelerated wear. The desired goal was to achieve component wearout in approximately 24 hours, providing acceptable test times with pre-cursor signatures representative of normal wearout. The test facility and approach is described, along with failure criteria and test results. Although the scope of this effort was relatively limited, it revealed some potentially useful wear indicators, along with many areas of difficulty for which further effort is recommended.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.926
Threshold uncertainty score0.339

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.236
Teacher spread0.225 · 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