Example: Weibull Degradation Crack Propagation (Point Estimation): Difference between revisions
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These values can now be substituted into the underlying exponential model, solved for <math>x</math> or: | These values can now be substituted into the underlying exponential model, solved for <math>x</math> or: | ||
<center><math>x=\frac{\text{ln}(y)-\text{ln}(b)}{a}</math></center> | |||
Using the values of <math>a</math> and <math>b</math> , with <math>y=30</math> , the resulting time at which the crack length reaches 30mm is then found for each sample: | Using the values of <math>a</math> and <math>b</math> , with <math>y=30</math> , the resulting time at which the crack length reaches 30mm is then found for each sample: |
Revision as of 18:28, 29 March 2012
Five turbine blades were tested for crack propagation. The test units are cyclically stressed and inspected every 100,000 cycles for crack length. Failure is defined as a crack of length 30mm or greater.
Following is a table of the test results:
Using degradation analysis with an exponential model for the extrapolation, determine the B10 life for the blades.
Solution
The first step is to solve the equation [math]\displaystyle{ y=b\cdot {{e}^{a\cdot x}} }[/math] for [math]\displaystyle{ a }[/math] and [math]\displaystyle{ b }[/math] for each of the test units. Using regression analysis, these values for each of the test units are:
These results are shown graphically in the next figure.
[math]\displaystyle{ }[/math]
These values can now be substituted into the underlying exponential model, solved for [math]\displaystyle{ x }[/math] or:
Using the values of [math]\displaystyle{ a }[/math] and [math]\displaystyle{ b }[/math] , with [math]\displaystyle{ y=30 }[/math] , the resulting time at which the crack length reaches 30mm is then found for each sample:
These times-to-failure can now be analyzed in the conventional manner. Assuming a two-parameter Weibull distribution and using the MLE estimation method, the distribution parameters are calculated as [math]\displaystyle{ \beta =8.055 }[/math] and [math]\displaystyle{ \eta =519,555. }[/math] Using these values, the B10 life is calculated to be 392,918 cycles. The degradation analysis tool in Weibull++ performs this type of analysis for you. The following figure shows the data as entered in Weibull++ for this analysis.
[math]\displaystyle{ }[/math]