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An Engine Dynamic Signal Testing System Based on Virtual Instrument Technology

2009· article· en· W2050038522 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

VenueApplied Mechanics and Materials · 2009
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Control Systems
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsSignal conditioningData acquisitionVirtual instrumentationComputer hardwareInstrumentation (computer programming)Portable computerSoftwareSIGNAL (programming language)Field (mathematics)Signal processingDigital signal processingComputer scienceInstrument DriverSampling (signal processing)Virtual instrumentPersonal computerData processingEngineeringEmbedded systemPower (physics)Electrical engineeringOperating systemDetector

Abstract

fetched live from OpenAlex

Aimed at the requirements of engine experimental research,a test system of engine dynamic signal was developed based on virtual instrument technology. The integral structure design of the system was given, the hardware is composed of sensors, signal conditioning module, high-speed data acquisition card and portable computer; the host computer software was developed with DASYLab, a virtual instrumentation tool. Its essential is to make good use of computer to achieve and extend functions of traditional instruments, by comprehensively using technologies of computer, digital signal processing, standard bus and software engineering method, functions of continuous multi channel sampling and multi type signal acquisition, and processing analysis were realized. The field test shows the system works reliably, development and application of this system can provide detailed experiment data and a new way in the field of engine power detection.

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: none
Teacher disagreement score0.690
Threshold uncertainty score0.732

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 head0.005
GPT teacher head0.182
Teacher spread0.178 · 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