Development of Automated Data Analysis Techniques for Eddy Current Testing Signals from Steam Generator Tubes in Nuclear Power Plants

Longer papers will not be dealt with. Shorter ones may not be informative enough to succeed. Eddy Current Testing (ECT) is widely adopted for flaw detection and sizing in steam generator (SG) tubes in nuclear power plants (NPP). ECT is really sensitive to flaws existed in SG tubes. However, it is also very sensitive to non-flaw parameters such as geometric distortion and electromagnetic properties of tubes. Therefore, ECT signal interpretation is a truly difficult task even to qualified data analyst (QDA), so there are high possibilities of mis-interpretation of ECT signals in practical field inspection. To address such difficulty, automated data analysis software is increasingly adopted. Recently, we have successfully developed a new bobbin coil ECT data analysis software, namely "ECT-IDS (Eddy Current Testing Intelligent Data Screening)," which can detect flaws in SG tubes even around supporting structure regions. To demonstrate performance of the developed software, we have applied the software to detecting flaws in the QDA training data sets which contain real ECT inspection signals from thinning, pitting, wear and IGA/SCC