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Adhesively bonded composite joints can develop voids and porosity during fabrication, leading to stress concentration and a reduced load-carrying capacity. Hence, adhesive porosity analysis during the fabrication is crucial to ensure the required quality and reliability. Ultrasonic-guided wave (UGW)-based techniques without advanced signal processing often provide low-resolution imaging and can be ineffective for detecting small-size defects. This article proposes a damage imaging process for adhesive porosity analysis of bonded composite plates using UGWs measured by scanning laser Doppler vibrometer (LDV). To implement this approach, a piezoelectric transducer is mounted on the composite joint specimen to generate UGWs, which are measured over a densely sampled area. The signals obtained from the scan are processed using the proposed signal processing in different domains. Through the utilization of filter banks in frequency and wavenumber domains, along with the root-mean-square calculation of filtered signals, damage images of the adhesive region are obtained. It has been observed that different filters provide information related to different void sizes. Combining all the images reconstructed by filters, a final image is obtained which contains damages of various sizes. The images obtained by the proposed method are verified by radiography results and the porosity analysis is presented. The results indicate that the proposed methodology can detect the pores with the smallest detectable pore area of 2.41 mm^2, corresponding to a radius of 0.88 mm, with an overall tendency to overestimate the pore size by an average of 11%.
Uncertainty quantification of multimodal surface wave inversion using artificial neural networks
(2023)
An inversion of surface waves dispersion curves is a non-unique and ill-conditioned problem. The inversion result has a probabilistic nature, which becomes apparent when simultaneously restoring the shear wave (S-wave) velocity and layer thickness. Therefore, the problem of uncertainty quantification is relevant. Existing methods through deterministic or global optimization approaches of uncertainty quantification via posterior probability density (PPD) of the model parameters are not computationally efficient since they demand multiple solutions of the inverse problem. We present an alternative method based on a multi-layer fully connected artificial neural network (ANN). We improve the current uni-modal approach, which is known from publications, to multi-modal inversion. The learned ANN maps the phase velocity dispersion curves to values of the S-wave velocity and layers thickness. To estimate the uncertainties, we adapt the Monte-Carlo simulation strategy and project onto the resulting velocity model both frequency-dependent data noise and inverse operator errors, which are evaluated by the prediction of the training data set. The proposed combination of surface waves data processing methods, configured with each other, provides a novel surface waves multi-modal dispersion data inversion and uncertainty quantification approach. We first test our approach on synthetic experiments for various velocity models: a positive velocity gradient, a low-velocity layer and a high-velocity layer. This is done considering uni-modal inversion at first and then compared to the multi-modal inversion. Afterwards, we apply our approach to field data and compare resulting models with the body S-wave processing by the generalized reciprocal method (GRM). The experiments show high-potential results using ANN yields the possibility to accurately estimate PPD of restored model parameters without a significant computational effort. The PPD-based comparison demonstrates advantages of a multi-modal inversion over uni-modal inversion. The trained ANN provides reasonable model parameters predictions and related uncertainties in real-time.
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.
This thesis investigates ultrasonic guided waves (GW) in multi-layered plates with the focus on higher order modes. The aim is to develop techniques for hybrid structures such as of adhesive bonds and composite pressure vessels (COPV) which are widely used in automotive and aerospace industries and are still challenging to inspect non-destructively. To be able to analyse GW, numerical methods and precise material properties are required. For this purpose, an efficient semi-analytical approach, the Scaled Boundary Finite Element Method, is used. The material properties are inferred by a GW-based optimisation procedure and a sensitivity study is performed to demonstrate the influence of properties on GW. Then, an interesting feature, called mode repulsion, is investigated with respect to weak and strong adhesive bonds. The results show that the coupling between two layers influences the distance between coupled modes in a mode repulsion region, thus allowing for the characterisation of adhesive bonds. At next, wave-damage interaction is studied in the hybrid structure as of the COPV. Results show that the wave energy can be concentrated in a certain layer enabling damage localisation within different layers. Further investigations are carried out on the hybrid plate with an impact-induced damage. Two well-known wavenumber mapping techniques, which allow to quantify the damage in three dimensions, are implemented and their comparison is done for the first time.
Water management in proton-exchange membrane fuel cells (PEMFCs) is critical for efficient operation. However, in-situ measurements of the water distribution in an operating PEMFC are challenging. In this study, we investigate key aspects of ultrasonic guided wave (UGW) propagation through the bipolar plate of a PEMFC using 3D scanning laser Doppler vibrometry (3D LDV). Our results provide insights for the design and optimization of UGW-based sensor systems for water detection in PEMFCs.
Wavefield measurements by a scanning laser Doppler vibrometer are generally carried out in a cartesian coordinate. As a piezoelectric transducer generates Lamb waves following radial paths, the use of a polar coordinate can be a suitable alternative to the use of a cartesian coordinate. Therefore, in the proposed method, using a single transducer placed on the center of the specimen, the measured wavefields are transformed into polar coordinates, making several identical radial line inspections from the center in a direction of incident waves. Taking advantage of the properties of the polar coordinates, a signal processing technique is proposed through a frequency-wavenumber filtering process in these coordinates. In this technique, by using proper filters, unwanted wave modes of the incident wave along with all reflected waves are filtered out. In addition, the conventional features of RMS and Euclidean distance are adapted for the polar coordinate system to image the bonded plate. The proposed signal processing and damage imaging are first introduced through a numerical simulation. Then, the performance of the proposed technique is presented by experimental measurements of two specimens including adhesively bonded carbon fiber-reinforced plastic composite plates and bonded aluminum plates.
Klebeverbindungen sind aus vielen Anwendungen wie dem Leichtbau nicht mehr wegzudenken. Durch die Verklebung gleicher oder ungleicher Materialien entstehen viele Vorteile gegenüber konservativen Fügeverfahren. Jedoch stellen schwache Haftfestigkeiten eine sehr unbeliebte Fehlerart dar, die schlecht zu detektieren sind und zu einem frühzeitigen Versagen der Verklebung bei vergleichsweise geringen Belastungen führen können. Aufgrund hoher Sicherheits- und Qualitätsansprüche wird die Haftfestigkeit dieser Verbindungen jedoch noch immer zerstörend geprüft. Zufriedenstellende zerstörungsfreie Verfahren, um Haftfestigkeiten zu prüfen, sind nicht vorhanden und Thema gegenwärtiger Forschung. Ein Ansatz, der in diesem Projekt verfolgt wird, liegt in der Verwendung geführter Ultraschallwellen.
Hierzu wird anhand von Simulationen mittels der Scaled Boundary Finite Element Methode gezeigt, dass die gezielte Auswertung bestimmter Bereiche des Dispersionsdiagrams, den sogenannten vermiedenen Kreuzungen (engl. mode repulsion regions), eine Charakterisierung der Haftfestigkeiten zulassen könnten. Dies liegt darin begründet, dass die mittleren mechanischen Belastungen der Kleberschicht in diesen Bereichen ein lokales Maximum aufweisen und daher eine erhöhte Sensitivität auf Materialänderungen haben. Es wird gezeigt, wie sensitiv diese Bereiche auf Materialänderungen in der Klebergrenzschicht sind und welche potenziellen Fehlergrößen existieren.
Klebeverbindungen sind aus vielen Anwendungen wie dem Leichtbau nicht mehr wegzudenken. Durch die Verklebung gleicher oder ungleicher Materialien entstehen viele Vorteile gegenüber konservativen Fügeverfahren. Jedoch stellen schwache Haftfestigkeiten eine sehr unbeliebte Fehlerart dar, die schlecht zu detektieren sind und zu einem frühzeitigen Versagen der Verklebung bei vergleichsweise geringen Belastungen führen können. Aufgrund hoher Sicherheits- und Qualitätsansprüche wird die Haftfestigkeit dieser Verbindungen jedoch noch immer zerstörend geprüft. Zufriedenstellende zerstörungsfreie Verfahren, um Haftfestigkeiten zu prüfen, sind nicht vorhanden und Thema gegenwärtiger Forschung. Ein Ansatz, der in diesem Projekt verfolgt wird, liegt in der Verwendung geführter Ultraschallwellen.
Hierzu wird anhand von Simulationen mittels der Scaled Boundary Finite Element Methode gezeigt, dass die gezielte Auswertung bestimmter Bereiche des Dispersionsdiagrams, den sogenannten vermiedenen Kreuzungen (engl. mode repulsion regions), eine Charakterisierung der Haftfestigkeiten zulassen könnten. Dies liegt darin begründet, dass die mittleren mechanischen Belastungen der Kleberschicht in diesen Bereichen ein lokales Maximum aufweisen und daher eine erhöhte Sensitivität auf Materialänderungen haben. Es wird gezeigt, wie sensitiv diese Bereiche auf Materialänderungen in der Klebergrenzschicht sind und welche potenziellen Fehlergrößen existieren.
Acoustic methods are ideally suited for determining the mechanical properties of different materials non-destructively. The availability of such methods is particularly important for fiber-reinforced polymers (FRPs) because their properties strongly depend on the manufacturing process and in-service conditions. Since FRPs are mostly used in thin-walled components, properties can be derived from the dispersion curves of ultrasonic guided waves (UGWs).
Our approach is based on an inverse procedure in which the numerically calcu-lated dispersion curves are fitted to the measured curves. The acquisition is done by applying a broadband piezoelectric transducer (PZT) to excite and a 3D laser Doppler vibrometer (3D LDV) to record the waves. Compared to the ap-proaches based on laser excitation, the PZT provides a better signal-to-noise ra-tio because more energy is brought into the structure. Whereas the 3D LDV compared to a 1D LDV or a PZT allows capturing in-plane and out-of-plane components and thus providing more dispersion information. Since the inverse procedure requires many iterations before elastic properties are retrieved, an ef-ficient tool for the calculation of the dispersion curves is necessary. For this, the Scaled Boundary Finite Element Method is used. All in all, a good agreement between theoretical and experimental curves is demonstrated.
Temperature Compensation Strategies for Lamb Wave Inspection using Distributed Sensor Networks
(2022)
The application of temperature compensation strategies is crucial in structural health monitoring approaches based on guided waves. Actually, the varying temperature influences the performance of the inspection system inducing false alarms or missed detection, with a consequent reduction of reliability. This paper quantitatively describes a method to compensate the temperature effect, namely the optimal baseline selection (OBS), extending its application to the case of distributed sensor networks (DSN). The effect of temperature separation between baseline time-traces in OBS are investigated considering multiple couples of sensors employed in the DSN. A combined strategy that uses both OBS and frequent value warning is considered. Theoretical results are compared, using data from two several experiments, which use different frequency analysis with either predominantly A0 mode or S0 mode data or both. The focus is given on the fact that different paths are available in a sensor network and several possible combination of results are available. Nonetheless, introducing a frequent value warning it is possible to increase the efficiency of the OBS approach making use of fewer signal processing algorithms. These confirm that the performance of OBS quantitatively agrees with predictions and also demonstrate that the use of compensation strategies improve detectability of damage.