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The value of imaging techniques in ultrasonic nondestructive inspection (NDI) to find and characterize defects in steel components has already been demonstrated. The imaging techniques based on the integral representation of the wave equation, the Rayleigh integrals for wave field extrapolation, are becoming feasible and attractive due to advances in array technology and due to faster computers. Known implementations are the total focusing method (TFM), the synthetic aperture focusing method (SAFT), and the inverse wave field extrapolation method (IWEX). In principle, these techniques compensate propagation effects from sources to a scatterer such as a defect and propagation effects from the scatterer to receivers. Currently, this approach is applied to wave fronts of single modes (pure longitudinal or pure transversal). In practice, multiple wave fronts from the scatterer will be received as a result of mode conversion. These arrivals will not have the same arrival time because of the difference in sound velocity between longitudinal and transversal waves. Images of mode converted waves are obtained by choosing the appropriate sound velocity that corresponds with the mode-converted scattered wave in the imaging process. Therefore, the nonmode converted waves will image as leakage artifacts in the mode-converted images, and vice versa. This may lead to false interpretations. In this paper, such artifacts will be identified and explained with the help of an analytical example. Measurements from steel test pieces with a 4 MHz linear array transducer with 64 elements will be used to demonstrate the artifacts. Furthermore, a procedure to predict the artifacts and the subsequent suppression from the input measurements will be presented and demonstrated.

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For a safe, reliable and efficient operation of facilities, knowledge and information of the condition and integrity of the assets are essential. Therefore, assets must be inspected on a regular base, preferably with non-destructive methods. Many of such methods are known in the industry (e.g. radiographic, magnetic, ultrasonic testing etc.), however their application is often restricted and the resulting data from the inspection is not adequate and/or sufficient for the asset integrity management. Due to advances in ultrasonic hardware and sensor technology, a novel approach for non-destructive testing based on ultrasonic imaging, IWEX, has been introduced. With this approach, an ultrasonic ‘fingerprint’ called a Full Matrix Capture (FMC) data set, can be measured. With the FMC data set representative 2D and 3D images from the interior of metal components (e.g. welds) can be re-constructed. For the inspection of such components, real time scans can be made in order to reveal possible flaws. The IWEX technology has already successfully been applied for the inspection of girth welds in newly constructed pipelines ([1], [2]). Furthermore, the method has recently been recognized by international codes and standards (ISO [3], ASME [4]), which opens the door for both new construction and in-service inspection applications in industrial facilities. In this paper, we will present the principles of ultrasonic imaging with the IWEX method. An example will be presented of an actual use case, concerning the inspection of welds in stainless steel pipes in an industrial facility. The welds contained cracks which were in some cases detectable with radiography, but height sizing was not possible. With the IWEX method, the cracks could reliably be detected, and it was possible to determine the crack heights. The height sizing accuracy was confirmed with known artificial targets in a representative reference block. Based on the accurate sizing results, it was possible to perform a fitness for service analysis which allowed a safe continuation of production in the facility. The use case of the IWEX method illustrates how this new technology facilitates improved maintenance strategies for the industry by enabling the possibility to obtain sufficient and accurate information during inspection. As a next steppingstone the 2D and 3D images can be stored digitally such that they can be used to monitor and predict the condition of the asset over time using novel analyses concepts such as pattern recognition by neural networks.