Roughness Investigations on In-Service High-Pressure Compressor Blades—Part I: An Automated Process for High-Fidelity Roughness Measurements

Abstract The 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.

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Publication Details

Journal
Journal of Turbomachinery
Published
2024-11-27
DOI
https://doi.org/10.1115/1.4067291
Primary Topic
Turbomachinery Performance and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Roughness Investigations on In-Service High-Pressure Compressor Blades—Part I: An Automated Process for High-Fidelity Roughness Measurements

Mirco Rostamian, Matthias Voigt, Ilias Vasilopoulos, Marcus Meyer et al.
Journal of Turbomachinery
Turbomachinery Performance and Optimization
article

Roughness Investigations on In-Service High-Pressure Compressor Blades—Part I: An Automated Process for High-Fidelity Roughness Measurements

Mirco Rostamian, Matthias Voigt, Ilias Vasilopoulos, Marcus Meyer, Ronald Mailach
article en

Abstract

Abstract The 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.

Journal of TurbomachineryVol. 147(8)
Rolls-Royce (Germany) (DE), Mahlo (Germany) (DE), Technische Universität Dresden (DE)
Bundesministerium für Wirtschaft und Energie
Openalex Percentile: Top 66%
Turbomachinery Performance and Optimization
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