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Record W3124334321 · doi:10.1115/ipc2020-9621

Microwave Chipless Resonator Strain Sensor for Pipeline Safety Monitoring

2020· article· en· W3124334321 on OpenAlexaff
Masoud Baghelani, Zahra Abbasi, Mojgan Daneshmand

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsResonatorAcousticsMaterials scienceChipless RFIDMicrowaveCapacitive sensingPipeline (software)Leakage (economics)Electronic engineeringEngineeringElectrical engineeringOptoelectronicsMechanical engineeringTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

Abstract Real-time hoop strain monitoring is known as an important parameter for the evaluation of pipeline safety and integrity. Internal corrosion and consequently variation of wall thickness directly reflects in hoop strain variation. In addition, leakage causes a pressure drop and strain reduction due to negative pressure wave. Due to their promising features such as extremely low cost, relatively high sensitivity, compatibility with harsh environmental conditions, distant and non-contact sensing with negligible power consumption, microwave resonator-based sensors achieved great deals of interest during the last decade. In this work, a chipless flexible microwave sensor for pipeline hoop strain real-time monitoring is presented. The sensor structure comprises a flexible chipless split ring microwave tag resonator attached to the pipeline and electromagnetically coupled to a pair of gap coupled transmission lines form the reader located at a certain distance from the tag strain sensor. Strain variations as the results of the mentioned pipeline defects change the overall length of the attached tag sensor which consequently causes a shift in its resonance frequency. For assuring the tag sensor to mechanically follow the strain variation of the pipeline, the Young modulus of its structural material should be much lower than that of the pipeline. This condition also important for the integrity of the sensor-pipe system because their connection will be accomplished by an adhesive. Since copper as the standard microwave conductive material is relatively highly stiff, it is not an appropriate candidate for such an important application. For addressing this issue, the chipless tag structure is fabricated by a conductive rubber layer in this work with extremely low Young modulus guaranteeing the length of the tag strain sensor to exactly follow the strain variation of the pipeline and forms a reliable and precise pipeline strain sensor. The spectrum of the tag sensor is reflected on the reader structure spectrum which could be measured to monitor the resonance frequency shift of the tag resulted from length variation of the tag sensor directly related to the pipeline strain fluctuation.

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 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 score0.869
Threshold uncertainty score0.838

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 head0.027
GPT teacher head0.236
Teacher spread0.209 · 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
Published2020
Admission routes1
Has abstractyes

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