Algorithm for turbocharger noise source recognition with speed identification from acoustic emission

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F26%3A0199102" target="_blank" >RIV/00216305:26210/26:0199102 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.utad.cz/koka25/" target="_blank" >https://www.utad.cz/koka25/</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Algorithm for turbocharger noise source recognition with speed identification from acoustic emission

Popis výsledku v původním jazyce

This paper presents an algorithm that can identify turbocharger (TC) noise sources and estimate rotor speed using acoustic emission data. The method distinguishes between mechanical and aerodynamic noise by analysing frequency components and correlating them with artificially generated signals. A novel approach is introduced for estimating TC speed without direct sensor input, which relies on tone prominence and Gaussian pulse modelling. The algorithm improves accuracy by summing correlation coefficients across multiple signal windows, thereby reducing false positives. Once the speed has been determined, potential noise sources can be identified based on known frequency signatures. This technique enables the non-invasive diagnosis of TC noise behaviour, supporting improved acoustic comfort and regulatory compliance in automotive applications.

Název v anglickém jazyce

Algorithm for turbocharger noise source recognition with speed identification from acoustic emission

Popis výsledku anglicky

This paper presents an algorithm that can identify turbocharger (TC) noise sources and estimate rotor speed using acoustic emission data. The method distinguishes between mechanical and aerodynamic noise by analysing frequency components and correlating them with artificially generated signals. A novel approach is introduced for estimating TC speed without direct sensor input, which relies on tone prominence and Gaussian pulse modelling. The algorithm improves accuracy by summing correlation coefficients across multiple signal windows, thereby reducing false positives. Once the speed has been determined, potential noise sources can be identified based on known frequency signatures. This technique enables the non-invasive diagnosis of TC noise behaviour, supporting improved acoustic comfort and regulatory compliance in automotive applications.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

20301 - Mechanical engineering

Projekt

<a href="/cs/project/TN02000054" target="_blank" >TN02000054: Národní centrum kompetence inženýrství pozemních vozidel Josefa Božka</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů