## 5 Experimental Research on the Positioning of Armored Composite Materials
### Experimental Study on Multi-Damage Imaging Localization  
When multiple locations in armored composite materials are subjected to external impacts, damage incidents are not isolated. Often, multiple damages occur within the structure, making the monitoring of multi-damage scenarios vital. Multiple damages can lead to overlapping Lamb signals, and the Shannon continuous complex wavelet transform offers high time-frequency resolution capabilities. By applying the wavelet transform to Lamb wave signals and subsequently performing time-reversal focusing imaging, effective monitoring can be achieved. Building upon the testing conducted in the previous section, the acquisition parameters remained unchanged, and two damage locations were identified. The locations of the damages are detailed in Table 8.  
The operational procedure for the damage imaging localization experiment remained consistent with the previous section. Figure 11 depicts the time-domain plots of the response signals extracted by the Shannon continuous complex wavelet transform with a center frequency of \(\omega_{c}=50\) kHz from the excitation-sensing channels 1-2, 1-3, and 1-4 under both healthy and damaged states of the structure. From the figure, it is evident that the amplitude  
Figure 10: Imaging localization results for each damage location. (**a**) Damage 1; (**b**) damage 2; (**c**) damage 3; (**d**) damage 4; (**e**) damage 5. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Group** & **Simulated Damage 1** & **Simulated Damage 2** \\  & **Coordinates/mm** & **Coordinates/mm** \\ \hline Group 1 & (69, 86) & (34, 53) \\ Group 2 & (148, 135) & (99, 96) \\ Group 3 & (119, 82) & (134, 29) \\ Group 4 & (66, 137) & (54, 52) \\ Group 5 & (90, 90) & (90, 50) \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Coordinates of two simulated damage locations. of the damaged signal remains slightly smaller than that of the healthy signal during propagation. However, there is a significant phase shift, leading to an increased amplitude of the damage scattering signal obtained by subtracting the narrowband response signals of each sensing channel, as illustrated in Figure 12.  
The signal within the range of 0 to 0.3 ms from the damage scattering signal was chosen as the direct wave signal. The signal in this portion was processed by determining the distance from the sensor to each unit point \((x,y)\) within the monitoring area. The time  
Figure 11: The excitation-sensing channel response signals when the structure is in both the healthy and damaged states. (**a**) The time-domain plot of the response signal in excitation-sensing channels 1-2; (**b**) the time-domain plot of the response signal in excitation-sensing channels 1-3; (**c**) the time-domain plot of the response signal in excitation-sensing channels 1–4. Figure 12: The damage scattering signal. (**a**) The time-domain plot of the damage scattering signal in excitation-sensing channels 1–2; (**b**) the time-domain plot of the damage scattering signal in excitation-sensing channels 1–3; (**c**) the time-domain plot of the damage scattering signal in excitation-sensing channels 1–4. delay of the response signal was calculated, and the delayed damage scattering signal, obtained by reversing the time, was utilized. The corresponding amplitude value at each time was used as the pixel value of the image matrix. The image was then scanned with a step size of \(0.1\times 0.1\) mm to obtain the pixel values of all unit points. After normalizing the pixel values, the damage imaging map was obtained. Figure 13 displays the imaging results of the damage positions in each group. The areas with higher pixel values in the image indicate a higher likelihood of damage. On the right side of the figure, the damage imaging maps are shown after setting a threshold of 90%, with most pixels concentrated in a small ellipse at the location of the damage, indicating the relative size range of the damage.