## 3 Results
### Experimental Results  
A Teletest MK4 device [29], manufactured by Teletest branch of Eddify technology family in Cambridge (UK), was used in order to inspect an eight-inch schedule 40 steel pipe with a total length of six metres. The test tool included three rings of 24 linearly spaced thickness-shear (d15) transducers with 30-mm spacing, which are located 1.5 m away from the back end of the pipe. The device is capable of operating in pulse-echo mode with the operating frequency of 20 to 100 kHz, and maximum sampling frequency of 1 MHz. On the reception side, the individual sections received from each transducer is postprocessed in order to reduce the effect of echoes received from backward testing direction and flexural waves [5; 17; 30]. The schematic of the signal reception routes with this setup is shown in Figure 15.  
The algorithm was assessed using data gathered from real pipes with three different defect size of 2%, 3% and 4% CSA. The defects were introduced using a saw-cut by thinning the wall thickness of the pipe's circumference. The schematics of the defects and their approximate sizes are shown respectively in Figure 16 and Table 2.  
Figure 14: The final result (red line) overlaid on the time-domain signal (black line) from experimental test case with the excitation frequency of 38 kHz and defect size of 3% CSA. Figure 15: Torsional mode reception route for laboratory trials. Depending on the system specification and test specimen, the maximum excitation power achieved by using frequencies in the range of 34 to 42 kHz. As can be seen in Figure 1a, most of the created flexurals from conversion of torsional wave is highly dispersive in the lower frequency region. Since dispersion affects the power spectrum of the received signal, it is expected that this algorithm works better with lower frequencies. However, the final choice of excitation frequency is a trade-off between the capability of the system to excite the required waveform and having highly dispersive flexural waves. Furthermore, it should be noted that the reflected wave amplitude at different frequencies is generally dependent on the flaw geometry, and this could effect the detection capability at different frequencies. In order to illustrate this dependency, 10 different frequencies have been used varying from 30 to 50 kHz with steps of 2 kHz. The achieved SNR from each signal of experimental tests are demonstrated in Figure 17 and Table 3. As can be seen, 40 kHz achieved the best SNR in the tests; with a neglectable difference in the case of 2% CSA defect signal in comparison to other frequency (34 and 42 kHz). Nonetheless, all these defects are either close to the coherent noise level, which are generated by the unwanted flexural waves or are buried within it. Therefore, detecting these defects using normal inspection procedures without calling any outliers are challenging. Figure 18 shows the processed results from each of these test cases where (a) shows the amplitude of detection and (b) shows the amplitude of outlier in the test. Outliers in these tests are considered as any detection corresponding to regions where the signal from neither defect or pipe features is expected to be received. In this figure, each line represents a defect with different CSA size and the value zero represents no detection. Furthermore, it can be seen that the algorithm works best in frequency range of 34-42 kHz. With these frequencies, defects with sizes above 3% can be detected with minor or no outliers existing in the results. In lower frequencies, although the amplitude of outliers is smaller than most test cases, defects with sizes smaller than 4% CSA cannot be detected. On the other hand, frequencies above 42 kHz generally result in the detection of outliers with higher amplitudes, where when using 48 and 50 kHz, no defect can be detected. The main reason is the transfer function of the system, where it is not capable of generating the expected power spectrum for the excitation waveform.