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Paper des Monats
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Investigation of temperature effects on ultrasonic velocity in a prestressed concrete bridge model
(2022)
Ultrasonic measurements have recently been applied in the context of structural health monitoring in civil engineering. The ultrasonic method is very sensitive to environmental conditions and material property changes, which might be caused by prestress losses and loading effects on the bridge. However, it remains a challenge to identify the damage mechanisms causing structural property changes from the above mentioned factors influencing ultrasonics. The focus of this contribution is to investigate the correlation between ultrasonic velocities and temperature by the coda wave interferometry (CWI) analysis. Long-term monitoring of a prestressed concrete bridge model under field conditions was carried out to observe the effect of temperature. The homogeneous change in concrete caused by temperature was revealed by applying the CWI method. The threshold value of the best correlation coefficients for the linear regression of temperature and ultrasonic velocity changes was also studied. Experimental assessment will provide a ratio for temperature correction to evaluate the pre-stressing force decrease and its consequences on crack opening or extension.
Reliability assessment of Structural Health Monitoring (SHM) systems
poses new challenges pushing the research community to address many questions which are still open. For guided wave-based SHM it is not possible to evaluate the system performance without taking into account the target structure and applied system parameters. This range of variables would result in countless measurements.
Factors like environmental conditions, structural dependencies and wave characteristics demand novel solutions for performance analysis of SHM systems compared to those relying on classical non-destructive evaluation. Such novel approaches typically require model-assisted investigations which may not only help to explain and understand performance assessment results but also enable complete studies without costly experiments. Within this contribution, a multi input multi output approach using a sparse transducer array permanently installed on a composite structure to excite and sense guided waves is considered. Firstly, the method and the analysis of path-based performance assessment are presented considering an open-access dataset from the Open Guided Wave platform. Then, a performance analysis of a guided wave-based SHM system using Probability of Detection is presented. To explain some unexpected results, the model-assisted investigations are used to understand the physical phenomena of wave propagation in the test specimen including the interaction with damage. Finally, issues and future steps in SHM systems’ performance assessment and their development are discussed.
Performance assessment for GuidedWave (GW)-based Structural Health Monitoring (SHM) systems is of major importance for industrial deployment.
With conventional feature extraction methods like damage indices, pathbased probability of detection (POD) analysis can be realized. To achieve reliability quantification enough data needs to be available, which is rarely the case.
Alternatives like methods for performance assessment on system level are still in development and in a discussion phase. In this contribution, POD results using an Artificial Intelligence (AI)-based data analysis are compared with those delivered by conventional data analysis. Using an open-access dataset from Open Guided Wave platform, the possibility of performance assessment for GW-based SHM systems using AI-based data analysis is shown in detail. An artificial neural network (ANN) classifier is trained to detect artificial damage in a stiffened CFRP plate. As input for the ANN, classical damage indicators are used. The ANN is tested to detect damage at another position, whose inspection data were not previously used in training. The findings show very high detection capabilities without sorting any specific path but only having a global view of current damage metrics. The systematic evaluation of the ANN predictions with respect to specific damage sizes allows to compute a probability of correct identification versus flaw dimension, somehow equivalent to and compared with the results achieved through classic path-based POD analysis. Also, sensitive paths are detected by ANN predictions allowing for evaluation of maximal distances between path and damage position. Finally, it is shown that the prediction performance of the ANN can be improved significantly by combining different damage indicators as inputs.
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.
The largest percentage of component life under fatigue loading conditions is spent in the short crack regime and in the initial phase of long cracks. The use of Fracture Mechanics in the characterization of fatigue crack growth rate curves has proven to be a useful and adequate tool in the prediction of fatigue lifetimes as long as certain conditions are satisfied. All the above implies the need for a methodical and accurate procedure of assessment of the material response in order to achieve a reliable prediction of lifetime in components under safe conditions, based on the damage tolerance approach. It also highlights the need to analyse the response of increasingly reduced thicknesses, which, as time goes by, show greater differences with respect to those commonly studied and defined in standards and design guidelines, as well as to the experimental studies that can be found in the literature at present. Some examples of thin-walled components are turbine blades or certain additively manufactured parts where, additionally, variations in material properties can occur locally and should also be examined.
Toughening mechanisms and enhanced damage tolerant fatigue behaviour in laminated metal composites
(2022)
In the present study, fatigue crack growth (FCG) in a laminated metal composite (LMC) consisting of Al-based constituents with dissimilar strength was studied. Additionally, the FCG in both monolithic constituent materials was determined and a linear elastic rule of mixture (ROM) concept was calculated as a reference for the FCG of the laminated composite. Crack networks in the laminates were analyzed post-mortem by means of light microscopy and synchrotron X-Ray tomography (SXCT). Significantly reduced FCG rates for the LMC were found at elevated stress intensity ranges compared to both the monolithic constituents as well as the ROM concept. This is the result of the formation of a complex 3D crack network in the laminated architecture caused by the appearance of the two different toughening mechanisms a) crack deflection and b) crack bifurcation at the vicinity of the interfaces.
Robotergeführte Ultraschallprüfung von Gasturbinenschaufeln mit adaptiver TFM im ZfP 4.0-Umfeld
(2022)
Leit- und Laufschaufeln stationärer Gasturbinen sind im Betrieb anspruchsvollen Bedingungen ausgesetzt. Die Prüfung, Wartung und Reparatur der hochbelasteten Teile sind notwendig, um Sicherheit und Effizienz über längere Zeiträume zu gewährleisten. Eine der in diesem Prozess angewandten Methoden ist die Ultraschallprüfung.
Im Zuge der fortschreitenden Digitalisierung ist es das Ziel des Projektes MRO 2.0, den Aufbereitungsvorgang um digitale Prozesse zu erweitern und somit zu modernisieren. Eine der Aufgaben ist es, dabei anstelle der konventionellen Ultraschallprüfung eine Array-Technik mit rekonstruierenden Verfahren einzusetzen und eine automatisierte, digital eingebundene Methode im Rahmen von ZfP 4.0 zu entwickeln.
Um die Ist-Geometrie der Oberfläche und die verbleibende Wanddicke flächendeckend an den Turbinenschaufeln zu bestimmen, wird ein adaptives TFM Verfahren (Total Focusing Method) in Tauchtechnik eingesetzt, welches die Brechung der Schallwellen an der Grenzfläche zum Prüfkörper in der Rekonstruktion berücksichtigt. In der hierfür entwickelten Prüfanlage führt ein Roboterarm einen Array-Prüfkopf und scannt das Bauteil normal zur inspizierten Oberfläche. Somit kann ein 3D-Modell des Ist Zustandes des zu prüfenden Bauteils erstellt werden.
Spezielle Herausforderungen an die Aufgabe stellen die komplexe Geometrie des Prüfobjektes sowie dessen geringe und ortsabhängige Wanddicke dar. Ein weiterer Fokus liegt auf der Optimierung der Prüfparameter, Verbesserung der Prüfgeschwindigkeit sowie der Zuverlässigkeit der Methode.
In diesem Beitrag werden die während des Projektes entwickelte Methode und die im zweiten Projektjahr erarbeiteten Ergebnisse vorgestellt, mit dem Schwerpunkt auf die entwickelten Rekonstruktionsalgorithmen und den Versuchsaufbau.
Brillouin Optical Frequency Domain Analysis (BOFDA) is a powerful and well-established method for static distributed sensing of temperature and strain. Recently, we demonstrated a BOFDA system based on convolutional neural network which shortens the measurement time considerably. In this paper, we apply leave-one-out cross validation to evaluate the generalization performance and provide an unbiased and reliable machine learning model for a time-efficient BOFDA system.
Larvae and adults of Korynetes caeruleus (de Geer 1775) (Coleoptera: Cleridae) were collected from old churches and reared in the laboratory on Anobium punctatum (de Geer 1774) (Coleoptera, Ptinidea, formerly Anobiidae). Breeding success of K. caeruleus was low, but basic parameters of this species’ developmental cycle were identified. At 21 °C and 75 % relative humidity and a four-month cold period at 4 °C, the development of K. caeruleus from egg to adult appearance lasted 2 years. The pupal stage may be reached and completed after one and a half years. Feeding on larvae of A. punctatum by larvae of K. caeruleus was observed and consisted of a combination of sucking haemolymph and consuming body parts. The sickle-like mandibles of larvae of K. caeruleus penetrate the cuticle of prey larvae followed by pumping and sucking body movements. Adult beetles of A. punctatum were not attacked by K. caeruleus larvae. Feeding behavior of adult K. caeruleus was not investigated.
11 laser printers from 5 manufacturers were purchased in 2017 and tested for their UFP emissions. Size resolved sampling of the emitted particles was done with a 13 stage (30 nm to 10 µm) low pressure cascade impactor. The sampled particles were analysed for their chemical composition by thermal extraction (vaporization at 290°C) followed by GC-MS analysis. High boiling cyclic siloxanes (D10 to D16) were detected as constituents of UFP from laser printers. In comparison to measurements in 2008, aliphatic long-chain alkanes (C22 to C34) were detected additionally as chemical constituents of UFP from most of the tested printers and their amounts were higher than for cyclic siloxanes. Printers of one manufacturer showed very low UPF emissions compared to the other manufacturers.