Enhancement of Synthetic Aperture Focusing Technique (saft) by Advanced Signal Processing

The synthetic aperture focusing technique (SAFT) is a well-established method for improving the resolution of an ultrasonic image. A major shortcoming is the inherent assumption that the pulse reflected from a flaw has a spectral content that is independent of the flaw's location relative to the transducer. In this project, we address the issue by using SAFT combined with Wiener filtering and an angle dependant set of reference signals. This allows the image of the flaw to be reconstructed with less distortion. The signal processing schemes are applied to synthetic flaw signals, and then to real defects of the type found in girth welds of gas pipelines. The result is a marked sharpening of both lateral and depth resolution, such that time-of-flight calculations can be used to obtain accurate measures of defect height. Introduction: Ultrasonic nondestructive testing (NDT) is employed primarily in the detection of critical defects within mechanical or structural components. For safety and economic reasons, it is of great importance to be able to size flaws accurately. SAFT is a signal processing tool that aim at improving the accuracy of ultrasonic signals, thus leading to better sizing capabilities. SAFT synthesizes a large focused transducer by gathering data at various positions using a small unfocused transducer. A synthetic aperture focusing system will produce a narrow synthetic beam by the mean of a coherent summation of phase adjusted pulses (A-scans). Since the synthetic beam width is much smaller than the actual transducer beam width, SAFT greatly improves the lateral resolution and the signal-to-noise ratio of the raw B-scan. A way of improving the temporal resolution is to deconvolve the A-scans before applying the SAFT algorithm. Wiener filtering is known to be one of the most effective deconvolution techniques [1]. The backwall echo is usually used as a reference signal. In this paper we refer to this technique as SAFTD. SAFTD is essentially an application of SAFT processing on an image which has been deconvolved with a single, on-axis reference signal. It is a well known fact that the lower frequency components of a beam have a wider divergence angle than the higher frequency components. This fact can be visualized in figure 1 which shows the on-axis frequency spectrum of a ultrasonic beam superposed on its frequency spectrum at an angle of 15 ̊. Figure 1: Frequency spectrum of a transducer at two different values of θ The use of the on-axis signal as a reference for deconvolution becomes inappropriate when θ is large since the frequency spectrum is shifted toward the low frequencies. One way to tackle this problem is to use an angle dependent deconvolution technique in conjunction with SAFT (SAFTADD). The SAFTADD operates in close analogy to the SAFT. However, instead of using the raw measurement data to generate the corrected image, it deconvolves each A-scan with the angle-corrected reference signal. To accomplish this in a computationally efficient fashion, a set of reference signals is first generated by a numerical model for a range of oblique angles. The raw B-scan is then deconvolved with each reference signal in this set to generate a library of Bscans, each deconvolved with a signal corresponding to an oblique angle. Each uncorrected point becomes a function of t, and x as before, but also of θ, the angle of the reference signal with which the raw point was deconvolved (Figure 2). Modifying the SAFT scheme to take this into account yields SAFTADD. Figure 2: Schematic representation of SAFT using a θ dependent deconvolved B-scan The performance of SAFTADD is first evaluated under ideal conditions. To this end, a comparison between SAFT/SAFTD and SAFTADD was done on synthetic data which simulated a B-scan collected with a typical pulse-echo inspection system. The data was generated synthetically using the numerical model. The second set of tests aimed to determine whether the results of the first study would be duplicated under more realistic conditions with data collected experimentally. Results: SAFTADD implies that each A-scan must be deconvolved using an appropriate reference signal according to its angle of divergence θ. We thus need a numerical model than will generate these reference signals. This model, based on the application of Huygen’s principle and ray theory, can predict the displacement field produced by a piston transducer inside a sample. Figure 3 presents an example of the configuration and the coordinate system used for the calculations. Figure 3: Representation of a circular piston transducer