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Record W1481214304

Windscreen insertion loss in still air

2003· article· en· W1481214304 on OpenAlexvenueno aff
Richard J. Peppin

Bibliographic record

VenueCanadian acoustics · 2003
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsnot available
Fundersnot available
KeywordsMicrophoneAcousticsNoise (video)AttenuationElectrical impedanceInsertion lossEnvironmental scienceMaterials scienceComputer scienceOpticsEngineeringElectrical engineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

Microphone windscreens are used to attenuate wind noise.However, even in still air, windscreens have an impact due to the added impedance between the source and microphone.This impedance is not accounted for when the system is checked by the use of an acoustical calibrator or when used in the field.The proce dure for the characterization of the attenuation in still air has recently been addressed in ANSI SI. 17-2000 part 1.But to date, no commercial windscreens have been tested in accordance with that standard.One of the reasons may be because the precision of the procedure has not been determined, even though the results of a round robin and the results of the uncertainty determination are available.Some of the commonly used windscreens were tested in a small chamber approaching free-field conditions.The results of the tests of insertion loss from the non-standard method and those based on SI. 17 are presented here.It is shown that in some cases, the use of a windscreen can easily change the measurements using Type 1 instruments to Type 2 or worse.Without knowing information about a particular windscreen, the use of a windscreen in still air, can drastically change uncertainty of measurement.In moving air conditions can be expected to be even more severe. SOMMAIRELes écrans de protections des microphones sont employés pour atténuer le bruit de vent.Mais même en condition de vent faible, ces derniers ajoutent une impédance entre la source et le microphone qui n'est pas prise en compte lors de l'étalonnage ou lors de l'utilisation sur le terrain.La procédure pour la caractérisa tion de l'atténuation sous condition de vent faible a été récemment adressé dans la partie 1 de la norme ANSI S 1.17-2000.Mais jusqu'ici, aucun écran de protection commercial n'a été vérifié selon les recom mandations du standard.En partie à cause du fait que la précision de la procédure n'a pas encore été déter minée.Les résultats d'un round robin et de la détermination des incertitudes sont disponibles.En attendant, nous avons testé quelques modèles d'utilisation courante et d'autres dans une petite chambre dont les carac téristiques acoustiques approchent celles du champ libre.Nous présentons les résultats des deux méthodes: pertes par insertion obtenues par notre méthode non standard, et ceux obtenues par la méthode standard AINSI S 1.17.Nous prouvons que, dans certains cas, l'utilisation d'un écran protecteur peut facilement changer la précision de la mesure avec l'emploi d'instruments de type 1 en type 2 ou plus mauvais.L'emploi d'un écran protecteur en condition de faible vent sans la connaissance préalable des caractéristique peut rigoureusement affecter l'incertitude de la mesure.Dans des condition de vent modéré à élevé, nous anticipons des problèmes encore plus graves.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.212
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2003
Admission routes1
Has abstractyes

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