TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

Cavitation Erosion Monitoring by Acoustic Emission

Tutkimustuotos

Standard

Cavitation Erosion Monitoring by Acoustic Emission. / Ylönen, Markku.

Tampere University, 2020. (Tampere University Dissertations; Vuosikerta 203).

Tutkimustuotos

Harvard

Ylönen, M 2020, Cavitation Erosion Monitoring by Acoustic Emission. Tampere University Dissertations, Vuosikerta. 203, Vuosikerta. 203, Tampere University.

APA

Ylönen, M. (2020). Cavitation Erosion Monitoring by Acoustic Emission. (Tampere University Dissertations; Vuosikerta 203). Tampere University.

Vancouver

Ylönen M. Cavitation Erosion Monitoring by Acoustic Emission. Tampere University, 2020. (Tampere University Dissertations).

Author

Ylönen, Markku. / Cavitation Erosion Monitoring by Acoustic Emission. Tampere University, 2020. (Tampere University Dissertations).

Bibtex - Lataa

@book{417b23ec7eaa4989abb3e58c83daa6fb,
title = "Cavitation Erosion Monitoring by Acoustic Emission",
abstract = "Cavitation is the formation of vapor bubbles either in a static liquid or in a liquid flow due to a drop in static pressure. When these bubbles collapse, as a result of pressure recovery, they may damage adjacent surfaces. These events are major causes of damage and nuisance in hydro machines. Modern hydro turbines are often used to regulate power grids; therefore, they may be operated out of their designed range. The flow-related optimal operation is different from the economic optimal usage. Detecting and characterizing cavitation and assessing damage during operation can be difficult or even impossible. Acoustic emission (AE) measurements provide a way to measure cavitation without access to the flow, but interpreting the data is challenging. This thesis presents insights in the ways of treating the AE data both in characterizing individual pits created by cavitation impacts and in tracking the evolution of cavitation erosion. Additionally, the erosion rates of three turbine materials were compared, and the main reasons behind the differing erosion rates of two martensitic turbine steels were discovered. The same high-speed cavitation tunnel was used in all cavitation experiments. This thesis firstly presents a method for enveloping an AE waveform signal and for counting the peak voltage values. The resulting cumulative distributions were compared to those of cavitation pit diameters, and from this comparison, a connection was proposed between AE peak voltage value and pit diameter. The second result was the connection between cavitation cloud shedding frequency and erosion evolution. The process of demodulating high frequency AE signals effectively promotes the low frequency shedding. The shedding frequency increased with accumulating material loss, and it was concluded that this increase is due to geometry effects, namely surface roughness. In addition to the two proposed methods, it was found that the decisive factors in the differing erosion rates of the martensitic stainless steels are the prior austenite grain size, packet and block sizes and the retained austenite fraction. This thesis provides guidelines directly applicable, such as the martensitic steel classifying, and methods that require further development, if one wishes to utilize them in hydro machine cavitation monitoring instead of laboratory measurements in a cavitation tunnel. The main outcome is that AE is a potential way to monitor cavitation, with the important benefit of not requiring any access to the flow.",
author = "Markku Yl{\"o}nen",
year = "2020",
month = "1",
day = "17",
language = "English",
isbn = "978-952-03-1420-0",
volume = "203",
series = "Tampere University Dissertations",
publisher = "Tampere University",

}

RIS (suitable for import to EndNote) - Lataa

TY - BOOK

T1 - Cavitation Erosion Monitoring by Acoustic Emission

AU - Ylönen, Markku

PY - 2020/1/17

Y1 - 2020/1/17

N2 - Cavitation is the formation of vapor bubbles either in a static liquid or in a liquid flow due to a drop in static pressure. When these bubbles collapse, as a result of pressure recovery, they may damage adjacent surfaces. These events are major causes of damage and nuisance in hydro machines. Modern hydro turbines are often used to regulate power grids; therefore, they may be operated out of their designed range. The flow-related optimal operation is different from the economic optimal usage. Detecting and characterizing cavitation and assessing damage during operation can be difficult or even impossible. Acoustic emission (AE) measurements provide a way to measure cavitation without access to the flow, but interpreting the data is challenging. This thesis presents insights in the ways of treating the AE data both in characterizing individual pits created by cavitation impacts and in tracking the evolution of cavitation erosion. Additionally, the erosion rates of three turbine materials were compared, and the main reasons behind the differing erosion rates of two martensitic turbine steels were discovered. The same high-speed cavitation tunnel was used in all cavitation experiments. This thesis firstly presents a method for enveloping an AE waveform signal and for counting the peak voltage values. The resulting cumulative distributions were compared to those of cavitation pit diameters, and from this comparison, a connection was proposed between AE peak voltage value and pit diameter. The second result was the connection between cavitation cloud shedding frequency and erosion evolution. The process of demodulating high frequency AE signals effectively promotes the low frequency shedding. The shedding frequency increased with accumulating material loss, and it was concluded that this increase is due to geometry effects, namely surface roughness. In addition to the two proposed methods, it was found that the decisive factors in the differing erosion rates of the martensitic stainless steels are the prior austenite grain size, packet and block sizes and the retained austenite fraction. This thesis provides guidelines directly applicable, such as the martensitic steel classifying, and methods that require further development, if one wishes to utilize them in hydro machine cavitation monitoring instead of laboratory measurements in a cavitation tunnel. The main outcome is that AE is a potential way to monitor cavitation, with the important benefit of not requiring any access to the flow.

AB - Cavitation is the formation of vapor bubbles either in a static liquid or in a liquid flow due to a drop in static pressure. When these bubbles collapse, as a result of pressure recovery, they may damage adjacent surfaces. These events are major causes of damage and nuisance in hydro machines. Modern hydro turbines are often used to regulate power grids; therefore, they may be operated out of their designed range. The flow-related optimal operation is different from the economic optimal usage. Detecting and characterizing cavitation and assessing damage during operation can be difficult or even impossible. Acoustic emission (AE) measurements provide a way to measure cavitation without access to the flow, but interpreting the data is challenging. This thesis presents insights in the ways of treating the AE data both in characterizing individual pits created by cavitation impacts and in tracking the evolution of cavitation erosion. Additionally, the erosion rates of three turbine materials were compared, and the main reasons behind the differing erosion rates of two martensitic turbine steels were discovered. The same high-speed cavitation tunnel was used in all cavitation experiments. This thesis firstly presents a method for enveloping an AE waveform signal and for counting the peak voltage values. The resulting cumulative distributions were compared to those of cavitation pit diameters, and from this comparison, a connection was proposed between AE peak voltage value and pit diameter. The second result was the connection between cavitation cloud shedding frequency and erosion evolution. The process of demodulating high frequency AE signals effectively promotes the low frequency shedding. The shedding frequency increased with accumulating material loss, and it was concluded that this increase is due to geometry effects, namely surface roughness. In addition to the two proposed methods, it was found that the decisive factors in the differing erosion rates of the martensitic stainless steels are the prior austenite grain size, packet and block sizes and the retained austenite fraction. This thesis provides guidelines directly applicable, such as the martensitic steel classifying, and methods that require further development, if one wishes to utilize them in hydro machine cavitation monitoring instead of laboratory measurements in a cavitation tunnel. The main outcome is that AE is a potential way to monitor cavitation, with the important benefit of not requiring any access to the flow.

M3 - Doctoral thesis

SN - 978-952-03-1420-0

VL - 203

T3 - Tampere University Dissertations

BT - Cavitation Erosion Monitoring by Acoustic Emission

PB - Tampere University

ER -