Classification of Acoustic Emission Stochastic Signals for Defects Imaging, Signal Deconvolution Principle by Means of Time Reversal Symmetries with Biomedical and Industry Applications

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F24%3A00379495" target="_blank" >RIV/68407700:21340/24:00379495 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Classification of Acoustic Emission Stochastic Signals for Defects Imaging, Signal Deconvolution Principle by Means of Time Reversal Symmetries with Biomedical and Industry Applications

Popis výsledku v původním jazyce

This dissertation deals with two main topics - the classification of acoustic emission (AE) signals and the time reversal approach used for signal processing. First, several classification methods are described (Fuzzy Method, Support Vector Machines, Model Based Clustering Method) and emphasis is placed on the newly developed method based on ϕ-divergences called Divergence Decision Tree (DDT) and its supervised version Supervised Decision Divergence Tree (SDDT). The ϕ-divergences, coming from the informationtheoretic field, are also successfully used as the signal parameters (attributes) to distinguish signal spectra in our classification algorithms. These newly proposed approaches are subjected to the thorough quality testing and applied in several non-destructive testing (NDT) experiments (pressure vessel, bluntness of drill bits) carried out under laboratory conditions at the Czech Academy of Sciences. We develop the concept of robust distances and ϕ-divergences and this key property for applications has been tested in computer simulation under the set-up of minimum distance estimation. Secondly, the time reversal (TR) techniques in NDT are presented in this thesis. Some newly developed procedures are described such as deconvolution by means of time reversal acoustics, time reversal transfer and localisation of continuous AE sources. The proposed time reversal transfer is successfully verified by the experiment on two sections of the aircraft wing flange. The localisation of continuous AE sources is validated by the two experiments on thin aluminium and thick steel plates. Finally, the effectiveness of combining these main areas of our research (AE, TR, Divergences, and DDT) is demonstrated by means of ’bubble’ and the Ultra Contrast Agent (UCA) experiments in biomedical applications for the localisation and statistical classification of ultrasonic nonlinearities - scatterers in the water tank. Finally, the main areas of scatterers suspicious for tooth decays were found in the human tooth experiment.

Název v anglickém jazyce

Classification of Acoustic Emission Stochastic Signals for Defects Imaging, Signal Deconvolution Principle by Means of Time Reversal Symmetries with Biomedical and Industry Applications

Popis výsledku anglicky

This dissertation deals with two main topics - the classification of acoustic emission (AE) signals and the time reversal approach used for signal processing. First, several classification methods are described (Fuzzy Method, Support Vector Machines, Model Based Clustering Method) and emphasis is placed on the newly developed method based on ϕ-divergences called Divergence Decision Tree (DDT) and its supervised version Supervised Decision Divergence Tree (SDDT). The ϕ-divergences, coming from the informationtheoretic field, are also successfully used as the signal parameters (attributes) to distinguish signal spectra in our classification algorithms. These newly proposed approaches are subjected to the thorough quality testing and applied in several non-destructive testing (NDT) experiments (pressure vessel, bluntness of drill bits) carried out under laboratory conditions at the Czech Academy of Sciences. We develop the concept of robust distances and ϕ-divergences and this key property for applications has been tested in computer simulation under the set-up of minimum distance estimation. Secondly, the time reversal (TR) techniques in NDT are presented in this thesis. Some newly developed procedures are described such as deconvolution by means of time reversal acoustics, time reversal transfer and localisation of continuous AE sources. The proposed time reversal transfer is successfully verified by the experiment on two sections of the aircraft wing flange. The localisation of continuous AE sources is validated by the two experiments on thin aluminium and thick steel plates. Finally, the effectiveness of combining these main areas of our research (AE, TR, Divergences, and DDT) is demonstrated by means of ’bubble’ and the Ultra Contrast Agent (UCA) experiments in biomedical applications for the localisation and statistical classification of ultrasonic nonlinearities - scatterers in the water tank. Finally, the main areas of scatterers suspicious for tooth decays were found in the human tooth experiment.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

10307 - Acoustics

Projekt

<a href="/cs/project/LM2023061" target="_blank" >LM2023061: Výzkumná infrastruktura pro experimenty ve Fermilab</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

2024

Kód důvěrnosti údajů

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