## 3 Results and Discussion
### Cluster Analysis and Pattern Recognition
Immediately after crack initiation, burst-type AE signals appeared, representing the fatigue crack propagation. In addition, AE signals of cluster 3 are neither of the burst type nor the continuous type; these signals are similar to burst-type signals, albeit with a longer rise time and duration. The associated mechanism may be the shear crack fracture, which generates a shear wave that consumes most of the energy but has a low propagation velocity and a longitudinal wave that consumes less energy but has a high propagation velocity. The longitudinal wave and shear wave arrive at the AE sensor successively and then combine to form a combination-type signal that is similar to a burst type signal but has a relatively longer rise time and duration (see Figure 10e,f). This type of AE signal has been found previously In the studies of [PERSON] [39] and [PERSON] [53] and has been attributed to shear cracks. In other types of steel (316 LN [39] and 304L [54]), these three types of AE waveform characteristics can also be observed. To validate that the signals in cluster 3 are generated by shear crack fractures, the correlation between the RA and AF parameters is used. These two parameters are defined in Equations (7) and (8). RA is the ratio of rise time to peak amplitude and is measured in \(\upmu\)s/\(\upmu\). AF is the ratio of ringing count to duration and is measured in kHz. The AE signal, due to the shear crack fracture, has a high RA and a low AF; while the AE signal, due to the tensile crack fracture, has a low RA and a high AF [53; 55]. It can be found that cluster 3 signals distribute widely along the RA and have a small distribution range along the AF (see Figure 11), while cluster 1 signals are the opposites of cluster 3 signals. Therefore, it can be reliably concluded that the mechanism of cluster 3 signals is related to shear crack fractures:  
\[\text{RA}=\text{Rise time/Peak amplitude}, \tag{7}\]  
\[\text{AF}=\text{Ringing count/Duration}. \tag{8}\]  
Figure 9: Cluster analysis of G20 MnSQT and weld: (**a**) DB index; (**b**) proportion of each cluster. Overall, cluster 1 is associated with tensile crack fractures, with the most AE signals; cluster 2 is associated with cyclic plastic deformations before the crack tip, with the second most AE signals; and cluster 3 is associated with shear crack fractures, with the fewest AE signals. The typical signal of each cluster is converted to the frequency spectrum by incorporating fast Fourier transform (see Figure 12). Similar to the research of [PERSON] et al. [56], the frequency spectra of fatigue crack growth have three peaks. The frequencies of peaks 1, 2, and 3 are approximately 80 kHz, 150 kHz, and 280 kHz, respectively. Peak 2 has the largest magnitude, while the frequency of peak 1 exhibits a dense band composed of several peaks and has the second-largest magnitude. The dissimilarities between the frequency spectra of different clusters are not notable. For cluster 1, location 3 also exhibits a dense band, as does location 1; however, the magnitude is not excessively high. For clusters 2 and 3,  
Figure 10: Waveforms of typical AE signals in different clusters: (**a**) cluster 1 signals of G20 Mn5 QT; (**b**) cluster 1 signals of welds; (**c**) cluster 2 signals of G20 Mn5 QT; (**d**) cluster 2 signals of welds; (**e**) cluster 3 signals of G20 Mn5 QT; (**f**) cluster 3 signals of welds. location 3 has a significant peak in the dense band. Although the methodology of this research is based on experimental samples, the analysis method can also be applied to the potential practical implications of monitoring engineering structures.