Turbine blades for gas turbines&nbsp;are exposed to&nbsp;extreme&nbsp;working&nbsp;conditions in a demanding environment.&nbsp;Recurring&nbsp;inspection, maintenance and refurbishment&nbsp;of the heavily stressed parts is necessary to ensure both safety and efficiency, e.g.&nbsp;based on&nbsp;immersion ultrasound testing (UT).&nbsp;&nbsp;&nbsp;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&nbsp;digitalization. For this, the goal&nbsp;of this project&nbsp;is to go beyond conventional automated and manual&nbsp;UT&nbsp;testing techniques.&nbsp;&nbsp;The aim is to measure the actual geometry and wall thickness of the&nbsp;complex shaped&nbsp;parts by applying an adaptive TFM that takes into account the refraction of the ultrasonic waves at the transition from the&nbsp;couplant&nbsp;to the inspected part. In this&nbsp;setup&nbsp;the phased array probe is held by a robotic arm that allows the part to be scanned while remaining&nbsp;mainly&nbsp;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&nbsp;generated.&nbsp;&nbsp;The&nbsp;laboratory setup&nbsp;is equipped with a&nbsp;Vantage 64&nbsp;phased array instrument&nbsp;from&nbsp;Verasonics&nbsp;Inc. and an industrial robot from ABB.&nbsp;A&nbsp;64-element&nbsp;linear array probe operating at 10 MHz is attached to the robot.&nbsp;&nbsp;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.&nbsp; 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.&nbsp;&nbsp;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.&nbsp;&nbsp;

Adaptive Tfm Approach for Turbine Blade Testing in a Nde 4.0 Environment

Paper Proceedings: https://asmedigitalcollection.asme.org/qnde/QNDE2021/volume/85529

ASME 2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation (QNDE2021)

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