## 4 Conclusions  
In this paper, based on previous research, an identification method of debonding damage of HFSCW based on a UAV-LDV system is proposed. The established system enables UAVs to transport the LDV to high altitudes for operation rather than utilizing a fixed LDV which works with the assistance of a UAV. It solves the previous problem of relying on manual inspection for debonding damage, which was inefficient, costly, and risky. The new assessment indicator (SSD) based on wavelet packet band energy decomposition has the additional advantage of providing a visual representation of the precise location of the damage, which is a superior feature compared to traditional indicators such as first-order natural frequency. In addition, potential factors affecting the performance of the UAV-LDV system were investigated, including the arrangement of measuring points, measuring distance, noise level, and wind speed. The study demonstrated that a wider distribution of measurement points and closer proximity of the UAV to the curtain wall enhance the detection efficiency by increasing data density in assessment diagrams and \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{5}{c}{**Average of 1 st Order Natural Frequency (Hz)**} \\ \hline
**Numerical Simulation** & **Wind Speed (m/s)** & **Fixed Test** & **Error** & **Mobile Test** & **Error** \\ \hline \multirow{4}{*}{88.52} & 1.5 & 88.68 & 0.18\% & 85.41 & \(-\)3.51\% \\  & 3.0 & 88.97 & 0.51\% & 83.48 & \(-\)5.69\% \\ \cline{1-1}  & 5.0 & 88.13 & \(-\)0.44\% & 96.13 & 8.60\% \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of first-order natural frequency results of Condition 3. Figure 15: Comparison diagrams of SSD. reducing laser energy loss. The results demonstrate that despite the influence of ambient noise and wind speed on the system performance, the system is still able to provide accurate and reliable detection results under reasonable operating conditions. Compared with traditional methods, the UAV-LDV system has significant advantages. Firstly, the system is able to complete large-area inspection tasks in a shorter time, which greatly improves inspection efficiency. Secondly, the system realizes non-contact detection, avoiding the safety hazards in the traditional method. Finally, the SSD indicator is able to accurately identify the damage location, providing more intuitive damage detection results. The main innovations of the study include the introduction of a novel UAV-LDV system for damage detection in Hidden Frame-Supported Glass Curtain Walls, the development of a new SSD indicator that offers visualization benefits and outperforms conventional indicators, the investigation of potential factors affecting the UAV-LDV system's performance, the conduction of an indoor full-scale experiment to examine the efficiency of the novel approach and the provision of valuable guidelines for utilizing the UAV-LDV system to inspect glass curtain walls. The establishment of the UAV-LDV system provides a low-cost, remote method for the early warning of HFSGCW, similar to the health monitoring of bridges and building structures. The results of our study indicate that the proposed nine-point measuring arrangement method should be adopted. It is inadvisable to utilize the UAV-LDV system for the identification of damage in windy or noisy environments, given the potential for a reduction in accuracy. In the future, we will further optimize the wind resistance of the UAV-LDV system and methods to reduce noise interference and will integrate the system with other technologies, such as incorporating machine learning methods to further improve inspection accuracy and efficiency. Finally, more field tests will be conducted to verify the stability and reliability of the system under different environmental conditions. Conceptualization, H.Z. and T.G. ; methodology, H.Z. ; software, H.Z. and G.Z. ; validation, H.Z. ; investigation, H.Z. and G.Z. ; resources, T.G. ; data curation, H.Z., Z.H. and G.Z. ; writing--original draft preparation, H.Z.