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Record W3157519307 · doi:10.18280/jesa.540216

Arc Welding Current Control Using Thyristor Based Three-Phase Rectifiers Applied to Gas Metal Arc Welding Connected to Grid Network

2021· article· en· W3157519307 on OpenAlexvenueno aff
Omar Fethi Benaouda, Badreddine Babes, Mohamed Bouchakour, Sami Kahla, Azzedine Bendiabdellah

Bibliographic record

VenueJournal Européen des Systèmes Automatisés · 2021
Typearticle
Languageen
FieldEngineering
TopicWelding Techniques and Residual Stresses
Canadian institutionsnot available
Fundersnot available
KeywordsWeldingGas metal arc weldingWelding power supplyArc weldingThyristorMaterials scienceLaser beam weldingVoltageMechanical engineeringElectrical engineeringEngineeringFiller metalMetallurgy

Abstract

fetched live from OpenAlex

The purpose of the welding operation is to ensure the continuity of the materials to be assembled in large industrial sectors. This study aims to suggest a topology of the Thyristor based three-phase rectifiers applied to the Gas Metal Arc Welding (GMAW) process connected to the grid network, the output currents are controlled and using various pulsed forms such as square, annealing, and spike pulse operations and investigate and compare between the effects of the three references welding currents structures on the welding current, welding voltage, droplet diameter, and welding quality. To have the best pulse operation, the amplitude and frequency are kept the same for all operations, the application of meshing graphs in the references of welding currents structures, welding current, welding voltage, and droplet diameter can illustrate a clear comparison between them. The simulation results show that the square pulse operation is the best among them. The Single-Sided Amplitude Spectrum (SSAS) method is also applied to the welding current and droplet diameter of the three operations under slow and rapid droplet detachment rates to estimate the droplet detachment frequency. The results show the great success of the SSAS in estimating the precise frequency.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.026
GPT teacher head0.274
Teacher spread0.248 · 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.

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

Citations8
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal Européen des Systèmes AutomatisésSame topicWelding Techniques and Residual StressesFrench-language works237,207