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Main Title Slide
SRAS processing
Obtaining information from signals
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Digital signal processing
Signal for a single pixel
We know the signal is a measure of the SAW velocity.
We know so we need to extract the frequency of the signal to obtain .
How should we proceed?
Digital signal processing
Take the FFT?
For this example what is the frequency we should use?
How do we find this automatically?
Any comments on the acquisition choices for this signal?
Digital signal processing
Find the max and see what frequency it is at.
Here we would have:
How accurately do we know the frequency?
We used the peak frequency what is the error?
Digital signal processing
We could be out by almost a sample
Sample spacing is dF which is related to the total time of the signal we used (T).
Error would be
How can we improve this?
Digital signal processing
Fitting or zero padding could be used as discussed in Lecture 2
We tend to use zero padding as it is easier.
Example: zero pad to 2^13
New dF is 488KHz, new error is 11.7 m/s
Digital signal processing
That was the processing for a single point – we repeat that for every point in the scan to produce an image.
How do we know that a signal belongs to a specific point on the sample / pixel in the image?
Applications
Aerospace applications – why material microstructure is important?
Several important material properties are structure sensitive:
yield strength,
fracture toughness,
thermal conductivity
These are all sensitive to microstructure parameters, such as:
Mean grain size
Degree of randomness, (both size and orientation)
Clusters of grains all oriented in the same direction
Material production
Consistency in material properties during production
Changes in grain size, grouping of prefer orientation
Modifications to material
Forming of components and impact on microstructure
This sample had random grain structure before being formed into a new shape
Now you can se ‘flows’ in the grain structure so the mechanical properties of this part will differ from the input material
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