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Record W2129053147 · doi:10.5539/mas.v1n3p47

Research of X-ray Nondestructive Detection System for High-speed running Conveyor Belt with Steel Wire Ropes

2007· article· en· W2129053147 on OpenAlexaffvenue
Junfeng Wang, Changyun Miao, Yue Cui, Wei Wang, Lei Zhou

Bibliographic record

VenueModern Applied Science · 2007
Typearticle
Languageen
FieldEngineering
TopicAdvanced X-ray and CT Imaging
Canadian institutionsUniversity of Alberta
FundersNatural Science Foundation of Tianjin City
KeywordsNondestructive testingField-programmable gate arrayVirtexPowerPCComputer scienceSoftwareComputer hardwareReliability (semiconductor)Conveyor beltEmbedded systemImage processingEngineeringMechanical engineeringImage (mathematics)PhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

The principle of X-ray nondestructive testing (NDT) is analyzed, and the general scheme of the X-ray nondestructive testing system is proposed. The hardware of the system is designed with Xilinx!?s VIRTEX-4 FPGA in whichPowerPC and MAC IP core are embedded, and its peripheral circuits. The network communication software based on TCP/IP protocol, which runs on the hardware platform, is programmed by loading LwIP to PowerPC in XilKernal system. On the basis of analysing image processing algorithm, the image processing software running on the PC is programmed. The NDT of high-speed conveyor belt with steel wire ropes and network transfer function are implemented. It is a strong real-time system with rapid scanning speed, high reliability and remotely nondestructive testing function. The nondestructive detector can be applied to the detection of product line in industry.

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)0.001
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 score0.569
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.019
GPT teacher head0.274
Teacher spread0.255 · 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 designBench or experimental
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

Citations1
Published2007
Admission routes2
Has abstractyes

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