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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.
Turbine blades for gas turbines are exposed to extreme working conditions in a demanding environment. In-service inspection, maintenance and refurbishment of the heavily stressed parts is necessary to ensure both safety and efficiency, e.g. based on immersion ultrasound testing (UT).
In the course of NDE 4.0, the European project MRO 2.0 aims to innovate the maintenance, repair and overhaul of turbine blades by linking these with modern digital methods. For this, the goal of this project is to go beyond conventional automated and manual UT testing techniques.
The aim is to measure the actual geometry and wall thickness of the complex shaped parts by applying an adaptive TFM that takes into account the refraction of the ultrasonic waves at the transition from the coupling material (water) to the inspected part (steel). In this setup the phased array probe is held by a robotic arm that allows the part to be scanned while remaining mainly perpendicular to the inspected surface. In this way, even complex geometries can be inspected and a 3D model of the actual condition of the part can be created.
The laboratory setup is equipped with a Vantage 64 phased array instrument from Verasonics Inc. and an industrial robot from ABB. A 64 element linear array probe operating at 10 MHz is attached to the robot.
The focus is on optimizing resolution, reliability and inspection speed, as the reconstructed model will be fed to the digital twin at a later stage of the project and used for targeted repairs. In addition to enhancing the reconstruction algorithms, required probe geometry and the parameters needed to inspect turbine blades with partially thin walls and anisotropic materials will also be investigated.
This talk will describe the 3-year project and present the results of the first year. The main focus will be on the development of the reconstruction algorithms used and the experimental setup.
Nondestructive testing of gas turbine blades is essential for their maintenance and service process which is critical to ensure both safety and efficiency of these highly stressed parts. In this presentation, a novel ultrasonic testing method is explored in order to acquire part thickness information in the turbine blade’s airfoil. In established industry processes, the measurements are mainly carried out manually and only at a few specific positions of the inspected parts. The proposed method scans the part using a robot arm guiding an ultrasonic array sensor. For ultrasonic coupling to the complex-shaped surface geometry, the inspected part and sensor are immersed into water. A two-step TFM[1, 2] (Total Focusing Method) approach is used to reconstruct the outer and inner surfaces subsequently from the ultrasonic raw data, which are acquired using the FMC[3] (Full Matrix Capture) measurement principle. For each sensor position, the location and geometry of the outer surface is first identified and then used to create an image of an area inside the material. From that image, the inner surface is reconstructed. Finally, part thickness information is deducted from merging location data of inner and outer surface. The result is a high resolution, high precision mapping of the inspected part’s wall thickness.
Automated Wall Thickness Evaluation for Turbine Blades Using Robot-Guided Ultrasonic Array Imaging
(2024)
Nondestructive testing has become an essential part of the maintenance of modern gas turbine blades and vanes since it provides an increase in both safety against critical failure and efficiency of operation. Targeted repairs of the blade’s airfoil require localized wall thickness information. This information, however, is hard to obtain by nondestructive testing due to the complex shapes of surfaces, cavities, and material characteristics. To address this problem, we introduce an automated nondestructive testing system that scans the part using an immersed ultrasonic array probe guided by a robot arm. For imaging, we adopt a two-step, surface-adaptive Total Focusing Method (TFM) approach.
For each test position, the TFM allows us to identify the outer surface, followed by calculating an adaptive image of the interior of the part, where the inner surface’s position and shape are obtained. To handle the large volumes of data, the surface features are automatically extracted from the TFM images using specialized image processing algorithms. Subsequently, the collection of 2D extracted surface data is merged and smoothed in 3D space to form the outer and inner surfaces, facilitating wall thickness evaluation. With this approach, representative zones on two gas turbine vanes were tested, and the reconstructed wall thickness values were evaluated via comparison with reference data from an optical scan. For the test zones on two turbine vanes, average errors ranging from 0.05 mm to 0.1 mm were identified, with a standard deviation of 0.06–0.16 mm.
In this work we focus on our most recent studies to super resolution (SR) laser thermography. The goal of SR nondestructive testing methods is to facilitate the separation of closely spaced defects. We explain how to combine laser scanning with SR techniques. It can be shown that stepwise as well as continuous scanning techniques are applicable. Finally, we discuss the effect of experimental parameters and im-age processing techniques to find the optimal SR technique which leads to the highest reconstruction quality within laser thermography.
Using spatial and temporal shaping of laser-induced diffuse thermal wave fields in thermography
(2020)
The diffuse nature of thermal waves is a fun-damental limitation in thermographic nonde-structive testing. In our studies we investigated different approaches by shaping the thermal wave fields which result from heating. We have used high-power laser sources to heat metallic samples. Using these spatial and temporal shaping techniques leads to a higher detection sensitivity in our measurements with the infra-red camera. In this contribution we show our implementation of shaping laser-induced diffuse thermal wave fields and the effect on the defect reconstruction quality.