Adaptive Ultrasonic Imaging of Electric Resistance Welded Pipeline Seams

Imaging techniques using full matrix capture (FMC) ultrasonic NDE are well suited for in-service examination of electric resistance welded (ERW) pipe seams. We have been involved in developing an imagine technique since 2013 and presented results from Phase I at IPC in 2016 showing the system capable of detecting seam weld and SCC flaws and determining their orientation. The advantages over other methods such as phased array (PA) is the ability to image the flaw surface in addition to the flaw tip and corners where the flaw intersects the pipeline surface. This improves the ability to determine flaw orientation for discrimination of different types or crack-like features. The system produces UT images by overlaying multiple modes using reflections off the ID and OD pipe surface for ultrasonic illumination of the weld area from different directions. Using multiple modes produces a reflection off features regardless of flaw orientation from at least one of the modes. A complementary mode can then be used to size each feature by detecting the tips or ends of the feature from lower amplitude diffraction signals. Phase I used a model which assumed a cylindrical pipe shape. Real world use of this technique found limitations when pipe deviated from the assumed cylindrical shape such as severe offset plate edges, flat spots which can be the result of poor crimping adjacent the seam weld, or thickening of the seam caused by post weld heat treatment.

 

In Phase II a need for reduced sizing error led to improved calibration and more advanced processing. To compensate for the non-perfect nature of real pipe, a new adaptive IWEX technique was developed to improve focusing and alignment of the various modes using the actual geometry to construct better focusing laws. First the OD and ID surfaces are imaged and the resulting surfaces are used to construct focusing laws which adapt to changes in the OD and ID surfaces. Results are better aligned UT images with the ability to image complex flaws with changes in orientation, and the ability to discriminate complex flaws from multiple small flaws in the pipe. Results show improvements in pipe with the greatest improvements in pipe with the largest deviations from a cylindrical shape.Access the full article here.