Eddy current technique for predicting burst pressure
- Yorkville, IL
- Oak Park, IL
- Woodridge, IL
- Western Springs, IL
- Downers Grove, IL
A signal processing technique which correlates eddy current inspection data from a tube having a critical tubing defect with a range of predicted burst pressures for the tube is provided. The method can directly correlate the raw eddy current inspection data representing the critical tubing defect with the range of burst pressures using a regression technique, preferably an artificial neural network. Alternatively, the technique deconvolves the raw eddy current inspection data into a set of undistorted signals, each of which represents a separate defect of the tube. The undistorted defect signal which represents the critical tubing defect is related to a range of burst pressures utilizing a regression technique.
- Research Organization:
- Argonne National Laboratory (ANL), Argonne, IL
- DOE Contract Number:
- W-31109-ENG-38
- Assignee:
- The University of Chicago (Chicago, IL)
- Patent Number(s):
- US 6519535
- OSTI ID:
- 875048
- Country of Publication:
- United States
- Language:
- English
A novel signal processing technique for eddy-current testing of steam generator tubes
|
journal | May 1998 |
Neural networks for the classification of nondestructive evaluation signals
|
journal | January 1991 |
Similar Records
The application of neural network for the advancement of the eddy current testing
Steam generator Tube Integrity Program. Quarterly report, January 1--March 31, 1977. [PWR]
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