[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121179-en":3,"doc-seo-121179-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},121179,687197207639,"Asher","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","Explainable machine learning determines effects on the sound absorption coefficient measured in the impedance tube - Abstract","Measurements of acoustic properties of sound absorbing materials in impedance tubes show poor reproducibility, as demonstrated by round robin tests. Although the impedance tube method is standardized, definitions of the actual setup, specimen preparation, and related practical factors still introduce uncertainty. Using explainable machine learning, the study analyzes over 3000 absorption spectra from one impedance tube to identify setup parameters that most strongly influence the sound absorption coefficient, and the frequency ranges most affected.","MARCH 18 2021  \nExplainable machine learning determines effects on the sound absorption coefficient measured in the impedance tubea) 􀀈  \nSpecial Collection: Machine Learning in Acoustics  \nMerten Stender; Christian Adams; Mathies Wedler; Antje Grebel; Nobert Hoffmann  \nJ. Acoust. Soc. Am. 149, 1932–1945 (2021)  \n[https://doi.org/10.1121/10.0003755](https://doi.org/10.1121/10.0003755)  \n􀀪  \nView Online  \n􀀮  \nExport Citation  \nArticles You May Be Interested In  \nSound absorption by clamped poroelastic plates  \nJ. Acoust. Soc. Am. 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Am. 1 March 2021; 149 (3): 1932-1945.' and may be found at [https://doi.org/10.1121/10.0003755](https://doi.org/10.1121/10.0003755)  \n06 November 2024 12:36:25  \nARTICLE  \n...................................  \nExplainable machine learning determines effects on the sound absorption coefficient measured in the impedance tubea)  \nMerten Stender,1,b) Christian Adams,2,c) Mathies Wedler,1 Antje Grebel,2 and Nobert Hoffmann1,d)  \n1Dynamics Group, Mechanical Engineering, Hamburg University of Technology, Am Schwarzenberg-Campus, Hamburg 21073, Germany 2Mechanical Engineering Department, System Reliability, Adaptive Structures, and Machine Acoustics, Technical University of Darmstadt, Otto-Berndt-Straße, Darmstadt 64287, Germany  \nABSTRACT:  \nMeasurements of acoustic properties of sound absorbing materials in impedance tubes show poor reproducibility, which was demonstrated in round robin tests. The impedance tube measurements are standardized but lack precise definitions of the actual measurement setup, specimen preparation, and other factors that introduce uncertainty in practice. In this paper, machine learning models identify those factors that mostly affect the sound absorption coefficient from a large data set of more than 3000 absorption spectra measured in one impedance tube. The specimens are manufactured from one polyurethane foam, and different cutting technologies, different operators, different specimen diameters, different specimen thicknesses, and two different approaches to mount the specimens in the impedance tube are considered. Explainable machine learning techniques allow the identification and quantification of the most influential factors and, furthermore, the frequency ranges that are the most affected by the choice of these setup factors. The results indicate that besides the specimen thickness, also the operator affects the absorption coefficient by a directional and non-random relationship. Hence, it needs to be controlled carefully. The method proves to be a promising pathway for knowledge discovery from acoustic measurement data using explainability approaches for machine learning models.  2021 Acoustical Society of America.  \n[https://doi.org/10.1121/10.0003755](https://doi.org/10.1121/10.0003755)  \n(Received 16 November 2020; revised 19 February 2021; accepted 22 February 2021; published online 18 March 2021)[Editor: Peter Gerstoft] Pages: 1932–1945  \nI. INTRODUCTION  \nThe acoustic properties of porous materials, such as the sound absorption coefficient, are important to room acoustics design or noise control treatments as well as to determine material parameters of porous material models. The sound absorption coefficient describes the ratio of the absorbed sound power and the incident sound power. It is commonly measured by ","cbCaigDMV4Np3AyX","https://ap.wps.com/l/cbCaigDMV4Np3AyX","pdf",3477415,1,15,"English","en",105,"# Abstract\n# Introduction","[{\"question\":\"Why are impedance tube measurements of sound absorption often poorly reproducible?\",\"answer\":\"Reproducibility is limited by uncertainties in how the measurement setup is defined and implemented, including specimen preparation and other practical factors, despite the method being standardized.\"},{\"question\":\"What data and factors does the study analyze to explain the sound absorption coefficient?\",\"answer\":\"It uses explainable machine learning on a dataset of more than 3000 absorption spectra, varying specimen cutting technology, operators, specimen diameter, thickness, and mounting approaches while using one polyurethane foam material.\"},{\"question\":\"Which setup factor is identified as significantly affecting the absorption coefficient beyond specimen thickness?\",\"answer\":\"The operator also affects the sound absorption coefficient through a directional, non-random relationship, requiring careful control.\"}]","Explainable machine learning determines effects on the sound absorption coefficient measured in the impedance tube - Abstract | PDF",1785734233,38,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"explainable-machine-learning-determines-effects-on-the-sound-absorption-coefficient-measured-in-the-impedance-tube-abstract","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/explainable-machine-learning-determines-effects-on-the-sound-absorption-coefficient-measured-in-the-impedance-tube-abstract/121179/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why are impedance tube measurements of sound absorption often poorly reproducible?","Question",{"text":75,"@type":76},"Reproducibility is limited by uncertainties in how the measurement setup is defined and implemented, including specimen preparation and other practical factors, despite the method being standardized.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What data and factors does the study analyze to explain the sound absorption coefficient?",{"text":80,"@type":76},"It uses explainable machine learning on a dataset of more than 3000 absorption spectra, varying specimen cutting technology, operators, specimen diameter, thickness, and mounting approaches while using one polyurethane foam material.",{"name":82,"@type":73,"acceptedAnswer":83},"Which setup factor is identified as significantly affecting the absorption coefficient beyond specimen thickness?",{"text":84,"@type":76},"The operator also affects the sound absorption coefficient through a directional, non-random relationship, requiring careful control.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]