Depending of which type of cavitation is considered less aceitable, an operation point can be selected such which supresses it. This is illustrated in the graph below. In it, the percentage of the possible metal loss is shown for the case that the power is set at a specified value or above it - for the blade-tip cavitation, and at a specified value or lower than it - for the blade-surface cavitation. Setting the power at 19.8 MW eliminates the blade-surface cavitation and reduces the metal loss due to the blade-tip cavitation to a half of its full possible amount; setting the power at 21.1 MW does the oposite, it eliminates the blade-tip cavitation and reduces the blade-surface erosion to a half. A kind of an optimum is reached by operating the turbine at 20.4 MW. Then, both types of erosion are reduced below 20 % of their values which would result if driving the turbine equally often at the power values between 18 and 21.5 MW.
To minimise the total metal loss in a plant with two or more turbines, the test should be made on all turbines, and, in time intervals in which the full plant power is not required, distribute the load over the turbines apropriatelly.
•
Optimisation of turbine maintenance - To transform the test results into fully quantitative data on the erosion, an additional turbine-specific calibration of the erosion-rate data is needed. It can be acomplished by monitoring the cavitation intensities as in
(3) or the respective assessments of cavitation erosion rate throughout the time between two checks of metal losses in the subsequent overhauls. This delivers a constant of proportionality in the erosion/load-rule which makes possible the erosion prediction based on a planed operation schedule and thus enables turbine-maintenance optimisation. Here is the logic:
Having, acording to
(3), the mean global cavitation intensity at the operation O, I(O), or its segments related the groups of cavitation mechanisms, and denoting by
t
n the total time the turbine spents on the operation point O
n - the data which can be derived from those in a common operation log - one calculates
[Constant of proportionality C] = [Metal loss found in the calibration time interval T
calibration] ×
{∑
n t
n [I(O
n)]
k}-1, where ∑
n t
n = T
calibration
and thus
[Metal loss expected in the passed or future time interval T
operation with a given set of t
n and O
n]
= C
{∑
n t
n [I(O
n)]
k}, ∑
n t
n = T
operation.
This is a simple tool for the analysis or prediction of the operation variants with respect to cavitation erosion. It uses data from an introductory cavitation test and the data on operation and thus does not require permanent cavitation monitoring.
Obviously, if the operation - passed, future or combined - follows the same program as in calibration, thus if the t
n and O
n are idential, the forcasts are simple:
[Metal loss expected in T
operation] = [Metal loss found in T
calibration] × T
operation / T
calibration.
• Turbine improvement - The other test results illustrated above, in addition to (3), deliver details of the cavitation mechanisms and can be used to improve turbine cavitation quality. Concerning this task, these diagnostic results are the final point that can be reached by the vibro-acoustic means. For defining the modifications that might result in an improvement of the turbine cavitation characteristics, model tests or a CFD analysis are necessary. The on-site vibro-acoustic test can then be used to check the result. Due to the scale effects in the model-to-prototype transformation of the cavitation results and the inacouracy in machining, the results found on the prototype may differ from model predictions and can be considerd more reliable.
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