• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.7 no.3
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• pp.61-66
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• 2011

The integrity of the SG(Steam Generator) tubes has been challenged by numerous factors such as flaws, operation, atmosphere, inherently degraded materials, loose parts and even human errors. Of the factors, loose parts(or foreign materials) on the secondary side of the tubes can bring about volumetric defects and even leakage from the primary to the secondary side in a short period of time. More serious concerns about the loose parts are their unknown influx path and rapid growth rate of the defects affected by the loose parts. Therefore it is imperative to detect and characterize the foreign materials and the defects. As a part of the measures for loose part detection, TTS(Top of Tubesheet) MRPC(Motorized Rotating Pancake Coils) ECT has been carried out especially to the restricted high probability area of the loose part. However, in the presence of loose parts in the other areas, wide range loose part detection techniques are required. In this study, loose part standard tube was presented as a way to accurately detect and characterize loose part signals. And the SG tube ECT bobbin coil and MRPC ISI(In-service Inspection) data of domestic OPR-1000 and Westinghouse Model F(W_F) were reviewed and consequently, comprehensive loose part detection technique is derived especially by applying bobbin coil signals

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.1
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• pp.13-19
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• 2010

In this paper, we study a new estimation system for the prediction of steam generator tube defects. In the previous research works, defect size estimators were independently designed for each defect types in order to estimate the defect size. As a result, the structure of estimation system is rather complex and the estimation performance gets worse if the classification performance is degraded for some reason. This paper studies a new estimation system that does not require the classification of defect types. Although the previous works are expected to achieve much better estimation performance than the proposed system since it uses the estimator specialized in each defect, the performance difference is not so large. Therefore, it is expected that the proposed estimator can be effectively used for the case where the defect type classification is imperfect.