| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Laakso, Jarmo
Tampere University
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (7/7 displayed)
- 2023High-Entropy Carbides:Processing And Characterization
- 2023High-Entropy Carbides: Processing And Characterization
- 2020Estimation of Cavitation Pit Distributions by Acoustic Emissioncitations
- 2020Evaluation of Residual Stresses and Their Influence on Cavitation Erosion Resistance of High Kinetic HVOF and HVAF-Sprayed WC-CoCr Coatingscitations
- 2016Compression curve analysis and compressive strength measurement of brittle granule beds in lieu of individual granule measurementscitations
- 2015High temperature oxidation tests for the high velocity solution precursor flame sprayed manganese-cobalt oxide spinel protective coatings on SOFC interconnector steelcitations
- 2012High temperature oxidation behaviour of MNCO2O4 coating on crofer 22 APU manufactured by a novel solution precursor plasma spray process (SPPS)citations
Places of action
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article
Estimation of Cavitation Pit Distributions by Acoustic Emission
Abstract
International audience ; Cavitation erosion in hydraulic machinery, such as in turbines and pumps, often leads to significant reduction of the service life of the affected components, with serious consequences for their maintenance costs and operation efficiency. In this study, the potential contribution of acoustic emission (AE) measurements to the assessment of cavitation damage is evaluated from experiments in a cavitation tunnel. Stainless steel samples were exposed to cavitation and damage was characterized from pitting tests carried out on mirror-polished samples. The pits were measured using an optical profilometer and cavitation damage was characterized by pit diameter distribution. In parallel, AE time signal was measured directly from behind the samples. A dedicated signal-processing technique was developed in order to identify each burst in the AE signal and determine its amplitude. The AE amplitude distribution compares well with PVDF and pressure sensor measurements from literature. It is concluded that AE signal analysis can be used to monitor the formation of pits without visual examination of the damaged surface. This provides a basis for possible future applications of nonintrusive cavitation erosion monitoring in hydraulic machines, provided the findings remain true in a more complex environment.