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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 crans de protections des microphones sont employs pour attnuer le bruit de vent.Mais mme en condition de vent faible, ces derniers ajoutent une impdance entre la source et le microphone qui n'est pas prise en compte lors de l'talonnage ou lors de l'utilisation sur le terrain.La procdure pour la caractrisa tion de l'attnuation sous condition de vent faible a t rcemment adress dans la partie 1 de la norme ANSI S 1.17-2000.Mais jusqu'ici, aucun cran de protection commercial n'a t vrifi selon les recom mandations du standard.En partie cause du fait que la prcision de la procdure n'a pas encore t dter mine.Les rsultats d'un round robin et de la dtermination des incertitudes sont disponibles.En attendant, nous avons test quelques modles d'utilisation courante et d'autres dans une petite chambre dont les carac tristiques acoustiques approchent celles du champ libre.Nous prsentons les rsultats des deux mthodes: pertes par insertion obtenues par notre mthode non standard, et ceux obtenues par la mthode standard AINSI S 1.17.Nous prouvons que, dans certains cas, l'utilisation d'un cran protecteur peut facilement changer la prcision de la mesure avec l'emploi d'instruments de type 1 en type 2 ou plus mauvais.L'emploi d'un cran protecteur en condition de faible vent sans la connaissance pralable des caractristique peut rigoureusement affecter l'incertitude de la mesure.Dans des condition de vent modr lev, nous anticipons des problmes 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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score0.889

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 head0.012
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2003
Admission routes1
Has abstractyes

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