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IntroductionThe signal received from an ultrasound transducer contains information about the component on which the transducer is placed. When the amplitude of this signal is plotted on a colour scale against transducer position, a cross-section representation of the component is created; these are called B-scan images. B-scan images are an extremely useful tool to the NDT technician, allowing them to 'see' inside a component. B-scan images can be created by measuring the distance a single transducer has moved, or by using multiple element linear array transducers. As with many imaging systems, ultrasonic systems are not without their problems. As a consequence of the way sound waves propagate and behave, the resolution of the system will always be suboptimal. The oscillations of the crystal in the transducer create a wavelet, which contaminates the echo signals from the material under test. Also, due to beam divergence, echoes will be received from targets within the material under test that are not directly in the line of sight of the transducer. Due to this, the images created tend to exaggerate feature sizes and appear blurred.This paper proposes a three-step scheme of signal processing measures to increase the resolution of these images. The first step uses a deconvolution method to improve the temporal or through-thickness resolution of the acquired images. The proposed deconvolution method uses a threshold to determine safe areas within the spectra of the signals to ensure stability. The second step uses a new BMW-SAFT to improve the spatial resolution in the scan axis of the images. The BMW-SAFT algorithm uses the Fraunhofer approximation to model the far field of the ultrasound beam, which is then used to determine the size of the aperture and the weights applied across the aperture during the focusing process. The final step utilises a statistical method to remove background speckle noise within the images. Speckle noise can come from many different sources, but it is noted that after the first step of the proposed process, the deconvolution method creates speckle noise within the image as a side effect. To test the methods proposed in this paper, a validated computer simulation model has been developed to generate single A-scans and entire B-scans. The simulation model will be described in Section 2. Section 3 describes the three different processing methods proposed by this paper and compares them to their more conventional counterparts. In Section 4, a discussion on the performance and suitability of these methods is provided. Simulation model Forward modelAn ultrasonic inspection system can be considered to be linear time invariant. The transfer function for the material under test can be considered as a series of Dirac delta functions. Each Dirac delta function will represent a feature within the part under test. These features will include any interfaces where there is a change in acoustic impedance, such as the far surface of the part, any defect indications or reflections caused by the grain st...

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The interpretation of ultrasonic B-scan images can be a time-consuming process and its success depends on operator skills and experience. Removal of the image background will potentially improve its quality and hence improve operator diagnosis. An automatic background noise removal algorithm is proposed, enabling the highlighting of defects and aiding the operator in the location and sizing of any anomalies. The method provides a means to successfully remove the background from a B-scan image.

Ultrasonic inspection of through-transmission is limited due to the inability to obtain defect depth information. Loss of signal is used as the only indicator, providing lateral defect information. This is often a problem in ultrasonic inspection. Radiographic acquisition techniques, where the X-ray source acts as the transmitter and the detector as the receiver, are conceptionally similar to ultrasonic through-transmission. In the latter, the tomography back-projection method is used to reconstruct images of an object that has been subjected to a minimum of 180° of rotation, to allow for full coverage of the item. In this paper, a novel approach based on back-projection is presented to improve image resolution and defect detectability. Two ultrasonic transducers in through-transmission configuration are utilised to capture data for image processing. The rotation of the transmitter and receiver is not possible in this set-up and, therefore, the reconstruction relies on the artificial generation of a limited rotation. Two probes are aligned either side of the material and are used to gather the ultrasonic signals. These signals are processed before the reconstruction algorithm is applied to them. Various processing and imaging reconstruction algorithms are explored, building on the basic back-projection method to obtain images that are better focused. This technique could be used within materials where there are high attenuation levels and, therefore, traditional pulse-echo is not feasible.