izpis_h1_title_alt

Avtonomni sistemi za klasifikacijo virov hrupa na osnovi prostorskega filtriranja
ID Murovec, Jure (Author), ID Prezelj, Jurij (Mentor) More about this mentor... This link opens in a new window

.pdfPDF - Presentation file, Download (14,18 MB)
MD5: 666CF4F359A30850C36D1B912C888403

Abstract
V tem doktorskem delu so predstavljeni rezultati raziskav, ki so omogočili razvoj napredne metode za merjenja hrupa. Postavljene so bile osnove za znanstveni preboj pri razumevanju človeške percepcije zvoka in razvoj aplikativnih metod za merjenje ter spremljanje hrupa z namenom izboljševanja življenskega prostora in razvoja okoljsko bolj sprejemljivih strojev ter naprav. Neposreden rezultat novih znanstvenih dognanj je štirikanalna mikrofonska antena z optimizirano geometrijo in novimi pripadajočimi algoritmi, s katerimi dosegamo razmerja signal-šum, ki presegajo vse komericalne sisteme za detekcijo smeri zvočnih virov. Z algoritmi smo poizkušali posnemati človekovo sposobnost prostorskega filtriranja akustične okolice. Ker smo se želeli čimbolj približati merilčevim dejanjem in slediti trendom meritvam hrupa v okolju, smo uporabili psihoakustične značilke, saj direktno opisujejo človeško dojemanje zvoka. Meritvam hrupa smo vpeljali pojem usmerjenosti imisije. Razvili smo tudi učinkovitejši algoritem za detekcijo smeri prihoda zvoka ter predstavili modificirano rastočo samoorganizirajočo mrežo, s katero samostojno klasificiramo zvočne dogodke. Prototipni sistem je bil preizkušen v realnem okolju.

Language:Slovenian
Keywords:mikrofonska antena, klasifikacija virov, samoorganizirajoče mreže, lokalizacija, avtomatizacija meritve hrupa
Work type:Doctoral dissertation
Typology:2.08 - Doctoral Dissertation
Organization:FS - Faculty of Mechanical Engineering
Place of publishing:Ljubljana
Publisher:[J. Murovec]
Year:2021
Number of pages:XXII, 167 str.
PID:20.500.12556/RUL-128016 This link opens in a new window
UDC:534.83:681.5:628.517(043.3)
COBISS.SI-ID:69145347 This link opens in a new window
Publication date in RUL:01.07.2021
Views:1359
Downloads:143
Metadata:XML RDF-CHPDL DC-XML DC-RDF
:
Copy citation
Share:Bookmark and Share

Secondary language

Language:English
Title:Autonomous systems for classification of noise sources based on spatial filtering
Abstract:
This doctoral thesis presents the results of research that enabled the development of a advanced method for measuring noise. This method will be the basis for an improved scientific research in the understanding of human sound perception and the development of applied methods for measuring and monitoring noise, with the aim of improving the environmental habitat and development of more acceptable machinery and equipment. The direct result of new scientific findings is a four-channel microphone antenna with optimized geometry and new associated algorithms with which we achieved signal-to-noise ratios that exceed all commercial systems for detecting the direction of sound sources. As we wanted to mimic human actions and track trends of environmental noise measurements, we used psychoacoustic features because they directly describe human perception of sound. We introduced the concept of immission directivity. We also developed a more efficient algorithm to detect the direction of sound arrival and introduced a modified growing self-organizing map for classification of different noise sources. The prototype system was tested in a real environment of noise measurements.

Keywords:microphone array, source classification, self-organizing maps, localization, automation, noise measurements

Similar documents

Similar works from RUL:
Similar works from other Slovenian collections:

Back