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Record W2108464329 · doi:10.1109/jsen.2009.2014419

Fiber Bragg Grating Sensors for Failure Detection of Flip Chip Ball Grid Array in Four-Point Bend Tests

2009· article· en· W2108464329 on OpenAlexaff
Hua Lu, Rasha Hussain, Ming Zhou, Xijia Gu

Bibliographic record

VenueIEEE Sensors Journal · 2009
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBall grid arrayFlip chipMaterials scienceFiber Bragg gratingSolderingStrain gaugePrinted circuit boardChip-scale packageSurface-mount technologyComposite materialOptoelectronicsOpticsElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

We have successfully demonstrated the application of fiber Bragg grating sensors to detect the solder interconnect debounding between flip chip ball grid array and printed circuit board in four-point bend tests. Four sensors, due to their small size, are surface-mounted on the four-corners of the ball grid array substrate, about 1 mm from the solder balls that allow more sensitive strain measurement under board flexure. The measured strain data are compared with the data from strain gauge, daisy chain resistance, and dye and pry test. The preliminary results show that the fiber sensors are capable of detecting the onset of solder joint fracture, strain relaxation, and extent of the failure.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.471
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.012
GPT teacher head0.232
Teacher spread0.220 · 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 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

Citations16
Published2009
Admission routes1
Has abstractyes

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