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This paper presents an automatic damage imaging technique by employing a signal processing approach based on applying hierarchically clustered filters across different domains. The technique involves time-frequency-wavenumber filter banks which are applied sequentially to ultrasonic guided wave (UGW) data. The study is conducted for a single lap joint composite specimen with a special focus on small voids which were formed due to manual adhesive component mixing. UGW data are acquired with a 3D Scanning Laser Doppler Vibrometer (LDV) over the scan area of the bonded plate. UGWs are excited at the central frequency of 100 kHz by a single piezoelectric transducer mounted on the surface of the single plate. Within each domain of time, frequency, and wavenumber, four filters are designed which results in 64 distinct filtered wavefields. From each filtered wavefield, an image is obtained by using root-mean-square (RMS) calculation of the signals. The obtained results are then combined to create a final, improved-resolution image of the scan area. The final image is compared to the image obtained through RMS calculation of full wavefield with interpolation through Delaunay triangulation and the image obtained by X-ray radiography. The results show that the smallest void that could be detected has a diameter of 2.14 mm.
Interdigital transducers (IDTs) are a well-known tool for excitation of surface acoustic waves. The use of IDTs is versatile, but they are most commonly employed as actuators for excitation of ultrasonic guided waves (UGWs). However, they are still a relatively new technology, which leaves many possibilities for future research, especially in the scope of newly emerging structural health monitoring (SHM) systems. IDTs offer low weight, design flexibility and beam directivity, which make them ideal candidates for employment in such systems.
Due to the IDTs’ and waves’ complexity, problems often cannot be described analytically, therefore they require numerical solutions and experimental validations. In this contribution, a novel, simple use of IDTs, in the scope of SHM is described. Firstly, numerical findings acquired with finite element method are presented. To validate those results, experiments in a plate-like waveguide are carried out. A good agreement between them is found. The results show the potential of the IDTs in yet another prospective application, which could be attractive for adoption in the future.
The dispersive properties of Lamb waves can be utilised for material characterisation because the frequency-wavenumber-relationship, as well as the group velocity, depend on material parameters. These dependencies make a non-destructive estimation of an elastic constant possible. This preliminary study investigates the sensitivity of dispersion curves caused by a change in elastic constants. The Scaled Boundary Finite Element Method is used to compute special dispersion curves, which show the sensitivity value of the frequency and group velocity as a colour value. This representation allows for easy identification of patterns and local effects. Two sets of dispersion curves are presented, one set for a steel plate and the other set for a plate made of a carbon fibre reinforced polymer. In general, we notice that the sensitivity often increases with the frequency and that higher-order modes seem to be more suitable for material characterisation. Moreover, specific modes respond to material changes while others are relatively unaffected, which must be taken into consideration for material characterisation.
Detailliertes Wissen über die mechanischen Eigenschaften verwendeter Materialien ist Grundvoraussetzung für viele ingenieurtechnische Aufgaben und Dienstleistungen. Zur Bestimmung der elastischen Materialparameter gibt es verschiedene klassische, zerstörende Prüfverfahren. Eine Möglichkeit der zerstörungsfreien Bestimmung liegt in der Auswertung von Messergebnissen, die auf Basis des Ausbreitungsverhaltens geführter Ultraschallwellen gewonnen wurden. Das Ausbreitungsverhalten geführter Ultraschallwellen kann mittels Dispersionsabbildungen dargestellt werden.
Um aus messtechnisch ermittelten Dispersionsabbildungen Rückschlüsse auf die Materialparameter zu ziehen, werden in der aktuellen Forschung verschiedene inverse Methoden diskutiert. Maschinelles Lernen und insbesondere Convolutional Neural Networks (CNNs) stellen eine Möglichkeit der automatisierten inversen Modellierung und Evaluierung von Bilddaten dar.
In diesem Beitrag wird gezeigt, wie das Ausbreitungsverhalten von geführten Ultraschallwellen unter Verwendung von CNNs genutzt werden kann, um die isotropen elastischen Konstanten einer plattenförmigen Struktur zu bestimmen. Hierfür werden die verwendeten Daten analysiert, das Preprocessing erläutert und eine grundlegende CNN-Architektur gewählt. Zur Auswertung des generierten Modells werden verschiedene Verfahren wie Gradienten-Mapping und die Visualisierung der verschiedenen Schichten vorgestellt. Die Anwendbarkeit der Methode wird anhand synthetischer Daten demonstriert.
In the context of Industry 4.0 and especially in the field of Structural Health Monitoring, Condition Monitoring and Digital Twins, simulations are becoming more and more important. The exact determination of material parameters is required for realistic results of numerical simulations of the static and dynamic behavior of technical structures. There are many possibilities to determine
elastic material parameters. One possibility of non-destructive testing are ultrasonic guided waves. For the evaluation of the measurement results, mostly inverse methods are applied in order to be able to draw conclusions about the elastic material parameters from analysing the ultrasonic guided wave propagation. For the inverse determination of the elastic material Parameters with ultrasonic guided waves, several investigations were carried out, e.g. the determination of the isotropic material parameters through the point of zero-groupvelocity or anisotropic material parameters with a simplex algorithm. These investigations are based on the evaluation of dispersion images. Machine learning and in particular Convolutional Neural Networks (CNN) are one possibility of the automated evaluation from Image data, e.g. classification or object recognition problems. This article shows how the dispersive behavior of ultrasonic guided waves and CNNs can be used to determine the isotropic elastic constants of plate-like structures.
Damit eine Simulationsrechnung, beispielsweise mit einer FEM-Software, eine ausreichend hohe Genauigkeit erreicht, muss vorausgesetzt werden, dass die Modellparameter eine sehr hohe Güte aufweisen. Die genaue Kenntnis der Materialparameter ist dabei von besonderer Bedeutung. Um diese Parameter bestimmen zu können, müssen die verwendeten Werkstoffe messtechnisch charakterisiert werden. Neben anderen Ansätzen sind dafür akustische Verfahren im Ultraschallbereich geeignet. Für dünnwandige und plattenförmige Materialien können aus den sich ausbreitenden geführten Wellen messtechnisch Dispersionskurven bestimmt und aus diesen die Materialparameter abgeleitet werden.
Da für die Signalverarbeitung und für Optimierungsaufgaben aktuell zunehmend Machine Learning Tools zum Einsatz kommen, stellt sich die Frage, ob diese Werkzeuge auch für die Ermittlung der Materialparameter aus den gemessenen Dispersionskurven eingesetzt werden können.
In der vorgestellten Untersuchung soll ein Convolutional Neural Network aufgestellt werden, welches aus Dispersionsbildern Muster extrahiert und aus diesen eine Schätzung für die Materialparameter ermittelt. Um die Machbarkeit dieses Ansatzes zu prüfen, werden zunächst nur isotrope Materialien betrachtet. Für das Netz werden mit der Scaled-Boundary-Finite-Element-Methode synthetische Daten für das Trainieren und Validieren generiert. Zusätzlich werden die Hyperparameter des neuronalen Netzes variiert, um ein optimales Model für die Schätzung zu finden. Anschließend kann das Netz mit experimentellen Daten getestet und das Ergebnis hinsichtlich der Genauigkeit bewertet werden.
Die Scaled Boundary Finite Elemente Methode (SBFEM) ist eine semi-analytische Methode, die speziell für Modellierung von geführten Wellen weiterentwickelt und optimiert wurde. Da nur den Rand der Rechendomäne diskretisiert wird, hat die SBFEM einen geringen Rechenaufwand. In diesem Beitrag wird die SBFEM benutzt, um die Ausbreitung geführter Wellen in einer Metall-Faserverbund-Werkstoffstruktur zu analysieren. Mittels der SBFEM ist es möglich, verschiede Fehlertypen, z.B. Ermüdungsrisse, Poren, Delaminationen, Korrosion, in das numerische Modell zu integrieren und damit Defekt-Mode-Wechselwirkung zu analysieren. Die Ergebnisse wurden für die Entwicklung einer Methode zur Zustandsüberwachung von Composite-Druckbehältern verwendet.
The Scaled Boundary Finite Element Method (SBFEM) is a semi-analytical method that shows promising results in modelling of guided ultrasonic waves. Efficiency and low computational cost of the method are achieved by a discretisation of the boundary of a computational domain only, whereas for the domain itself the analytical solution is used. By means of the SBFEM different types of defects, e.g. cracks, pores, delamination, corrosion, integrated into a structure consisting of anisotropic and isotropic materials can be modelled.
In this contribution, the SBFEM is used to analyse the propagation of guided waves in a structure consisting of an isotropic metal bonded to anisotropic carbon fibre reinforced material. The method allows appropriate wave types (modes) to be identified and to analyse their interaction with different defects. Results obtained are used to develop a structural health monitoring system for composite pressure vessels used in automotive and aerospace industries.
Lamb waves are widely used for non-destructive evaluation of material parameters as well as for detection of defects. Another application of Lamb waves is quality control of adhesive joints.
Researchers are currently investigating shear horizontal and zero-group velocity modes for characterisation of the adhesive bonding strength. In a new approach, Lamb wave mode repulsion is used to obtain the coupling strength between different layers to characterise the adhesive bonding strength. The modes of the individual layers become coupled in the multilayered systems forming particular regions, the so-called mode repulsion regions. This study investigates these modes and their interaction in two-layered plate-like structures with varying coupling strength both numerically, with the Scaled Boundary FEM, and experimentally
Damage Quantification in Aluminium-CFRP Composite Structures using Guided Wave Wavenumber Mapping
(2019)
The use of composite materials is associated not only with the advantages of weight reduction and improved structural performance but also with the risk of barely visible impacts or manufacturing damages. One of the promising techniques for the detection and characterisation of such damages is based on ultrasonic guided wave propagation and analysis. However, the multimodal nature and dispersive behaviour of these waves make their analysis difficult. Various signal processing techniques have been proposed for easier interpretation of guided wave signals and extraction of the necessary information about the damage. One of them is the wavenumber mapping which consists of creating a cartography of the wavenumber of a propagating mode over an inspected area, using a dense wavefield acquisition measured for example with a scanning laser Doppler vibrometer. This technique allows both the quantification of the in-plane size and the depth of damage, for example, impact-induced delamination in composite laminates.
In this contribution, wavenumber mapping is applied to a delaminated aluminium-CFRP composite structure which corresponds to composite-overwrapped pressure vessels used for storing gases in aerospace and automotive industries. The analysis of experimental data obtained from measurements of guided waves propagating in an aluminium-CFRP composite plate with impact-induced damage is performed. The output of the imaging is a three-dimensional representation of the delamination induced by the impact. Good agreement between conventional ultrasonic testing and guided wave damage mapping can be found.