A heuristic method for detecting and locating faults employing electromagnetic acoustic transducers

• Autorzy: Gómez C. Q. M. , García F. P. M. , Arcos A. J. , Cheng L. , Kogia M. , Mohimi A. , Papaelias M. A.

Identyfikatory

DOI

10.17531/ein.2017.4.1

Warianty tytułu

PL

Heurystyczna metoda wykrywania i lokalizowania usterek z wykorzystaniem elektromagnetycznych przetworników akustycznych

• Języki publikacji: EN

Abstrakty

EN

The objective of this paper is to demonstrate a novel signal processing for detection, identification and flaw sizing of structural damage using ultrasonic testing with Electromagnetic Acoustic Transducers (EMATs). Damage detection involves the recognition of a defect that exists within a structure. Damage location is the identification of the geometric position of the defect. Defect classification is the cluster of the damage type into multiple damage scenarios. In the absence of external interferences, a good measure of detectability of a flaw is its signal-to-noise ratio (SNR). Although the SNR depends on various parameters such as electronics used, material properties, e.g. homogeneity and damping, and flaw size, it can be improved using advanced signal processing. The main scientific novelties presented in this paper focus on filtering signal noise through advanced digital signal processing; incorporating wavelet transforms for image and signal representation enhancements; investigating multi-parametric analysis for noise identification and defect classification; studying attenuation curves properties for defect localisation improvement and flaw sizing and location algorithm development.

PL

Celem niniejszego artykułu jest omówienie nowatorskiego sposobu przetwarzania sygnałów w celu wykrywania, identyfikacji i oceny uszkodzeń strukturalnych przy użyciu ultrasonograficznych testów za pomocą elektromagnetycznych przetworników akustycznych (EMAT). Wykrywanie uszkodzeń polega na rozpoznaniu istniejących defektów wewnątrz danej struktury. Lokalizacja uszkodzeń sprowadza się do identyfikacji geometrycznego położenia defektu. Klasyfikacja defektu to klaster typu uszkodzenia w wielu scenariuszach uszkodzeń. W przypadku braku zewnętrznych zakłóceń, dobrym wskaźnikiem wykrywalności błędu jest stosunek sygnału do szumu (SNR). Pomimo tego, że SNR zależy od różnych parametrów, takich jak użyta elektronika, właściwości materiału, np. jednorodność i tłumienie, a także wielkość wady, wskaźnik ten można poprawić przy użyciu zaawansowanego przetwarzania sygnałów. Główne nowe zagadnienia naukowe przedstawione w niniejszym artykule skupiają się na filtrowaniu szumu sygnału za pomocą zaawansowanego przetwarzania sygnału cyfrowego, w tym wykorzystując transformaty falkowe w celu ulepszenia obrazu i sygnału; badanie analizy wieloparametrycznej w celu identyfikacji szumów i klasyfikacji defektów; badanie właściwości krzywych osłabiania w celu sprawniejszego wykrywania i oceny wad oraz rozwoju algorytmu lokalizacji.

Słowa kluczowe

EN

fault detection and diagnosis; electromagnetic acoustic transducers (EMAT); wavelet transforms; non destructive test; guided waves

PL

wykrywanie i diagnozowanie wad; elektromagnetyczne przetworniki akustyczne; EMAT; transformaty falkowe; badania nieniszczące; fale prowadzone

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2017
• Tom: Vol. 19, no. 4
• Strony: 493--500
• Opis fizyczny: Bibliogr. 34 poz., rys., tab.

Twórcy

autor

Gómez C. Q. M.

• Ingenium Research Group European University of Madrid Tajo street, c Building, c4 office, 28670, Villaviciosa de Odon Madrid, Spain

autor

García F. P. M.

• Ingenium Research Group Castilla-la Mancha University Politecnic Building, Camilo José cela Street, 13071 Ciudad Real, Spain

autor

Arcos A. J.

• Ingenium Research Group Castilla-la Mancha University Politecnic Building, Camilo José cela Street, 13071 Ciudad Real, Spain

autor

Cheng L.

• Brunel Innovation Centre TWi, Granta Park, Granta Park Cambridge, cB21 6al United Kingdom

autor

Kogia M.

• Brunel Innovation Centre TWi, Granta Park, Granta Park Cambridge, cB21 6al United Kingdom

autor

Mohimi A.

• Brunel Innovation Centre TWi, Granta Park, Granta Park Cambridge, cB21 6al United Kingdom

autor

Papaelias M. A.

• School of Metallurgy and Materials University of Birmingham Edgbaston Birmingham, B15 2TT United Kingdom

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