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Record W2033284883 · doi:10.1108/01439910710727469

An autonomous self contained wall climbing robot for non‐destructive inspection of above‐ground storage tanks

2007· article· en· W2033284883 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

VenueIndustrial Robot the international journal of robotics research and application · 2007
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsDalhousie University
Fundersnot available
KeywordsNondestructive testingRobotStorage tankEngineeringComputer scienceArtificial intelligenceMechanical engineering

Abstract

fetched live from OpenAlex

Purpose The aim of this research is to design a wall climbing robot (WCR) for the non‐destructive inspection (NDT) of the above‐ground storage tanks (ASTs) autonomously making the industrial inspection and maintenance tasks safer. Design/methodology/approach A WCR is designed that can be equipped with any NDT sensor. It uses permanent magnets as an adhesion mechanism to crawl over the steel tank walls. A surface coverage algorithm is proposed for the WCR to scan the AST wall surfaces autonomously with the NDT sensors to perform the necessary inspection tasks. Findings The proposed surface coverage algorithm performs the complete coverage of the AST walls under different obstacle configurations. It has been tested and demonstrated in simulations. Originality/value A surface coverage algorithm is proposed for the WCR to perform the non‐destructive inspection of the ASTs autonomously. It can also be used in applications like cleaning glass building and painting ship hulls, etc.

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)0.002
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 score0.721
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
Research integrity0.0000.001
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 head0.055
GPT teacher head0.353
Teacher spread0.298 · 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