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contributor authorVasilopoulos, Ilias
contributor authorRostamian, Mirco
contributor authorVoigt, Matthias
contributor authorMeyer, Marcus
contributor authorMailach, Ronald
date accessioned2025-04-21T10:21:39Z
date available2025-04-21T10:21:39Z
date copyright1/13/2025 12:00:00 AM
date issued2025
identifier issn0889-504X
identifier otherturbo_147_8_081001.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4306020
description abstractThe two-part publication deals with roughness investigations on in-service high-pressure compressor (HPC) blades, both in terms of measurements and simulations. In this article (Part I), an automated process for performing detailed surface roughness measurements of the blades has been developed. Specifically, a highly accurate Alicona sensor (20x lens; capable of capturing roughness values down to 0.1μm) was combined with a pick-and-place robotic arm, and the system was trained to conduct roughness measurements on all the different rotor blades of a 10-stage HPC. First, the Alicona measuring device is validated against a NanoFocus device of similar accuracy. Then, a detailed measurement of the roughness on the suction and pressure side of Rotor 2 is demonstrated, using a 100-point grid. This process is further accelerated by using a reduced number of measuring points. The location of those points has been determined by numerical optimization that aims at minimizing the error between a radial basis function (RBF)-based approximation model and the detailed measured roughness distribution. Finally, a summary of the roughness measurements through the entire HPC is given (rotors only; before and after cleaning of the blades at an ultrasonic bath) and the article ends with a discussion of the results.
publisherThe American Society of Mechanical Engineers (ASME)
titleRoughness Investigations on In-Service High-Pressure Compressor Blades—Part I: An Automated Process for High-Fidelity Roughness Measurements
typeJournal Paper
journal volume147
journal issue8
journal titleJournal of Turbomachinery
identifier doi10.1115/1.4067291
journal fristpage81001-1
journal lastpage81001-9
page9
treeJournal of Turbomachinery:;2025:;volume( 147 ):;issue: 008
contenttypeFulltext


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