## 3 Influence Factors of the UAV-LDV System
### Noise Level  
The LDV exhibits self-vibration caused by machinery, transportation, passersby, wind, etc. These natural noises can be mitigated by incorporating vibration sensors on the LDV and analyzing the combined data from them, or alternatively by using two LDVs together [54]. However, random noise from the environment affects the measuring accuracy, which necessitates further investigation. Four unilateral damaged conditions are used as examples to test the performance of the UAV-LDV system under different noise levels, as illustrated in Figure 9. The damage all occurs unilaterally, which distinguishes it from the four conditions depicted in Figure 6. In the case of unilateral damage, most of the structural sealants work properly, and the overall structure remains relatively stable. If noise levels significantly interfere with structural damage detection in this situation, more severely damaged conditions will further deteriorate. Therefore, the unilateral damaged conditions are chosen for testing. The damage lengths of the four conditions are intact, 1/4 length damaged, 1/2 length damaged, and completely damaged on one side. The measuring points are arranged according to the nine-point method presented in Section 3.2. Based on the results of the study in Section 3.3, the measuring distance was set to 1 m.  
During the test, to simulate the actual environment, a stereo system is established using two Apple HomePod minis to play the recorded construction noises with a frequency distribution range of 0-500 Hz, as shown in Figure 10. They are located 2 m apart and symmetrically distributed along the central axis of the specimen, 0.5 m away from it. This allows them to interfere with both the curtain wall vibration and the LDV test results, resulting in a more realistic simulation of ambient noise. A decibel meter is used to measure the ambient noise level, and the test is performed when the noise level reaches 20 dB, 30 dB, 40 dB, 50 dB, 70 dB, and 100 dB, respectively. Table 5 compares the average first-order natural frequencies obtained from the numerical simulations with the tests. The same panel was tested under different conditions with the same technique. The results indicate that the noise level has a significant impact on  
Figure 10: Test site setup. Figure 9: Testing conditions. (**a**) Condition 1. (**b**) Condition 2. (**c**) Condition 3. (**d**) Condition 4.  
the reliability of the UAV-LDV system. Even in the case of unilateral damage, the error in the first-order natural frequency always exceeds 5% or even 10%, and it will be larger for the cases with bilateral and multilateral damage where boundary failure is more severe. Consequently, to acquire first-order natural frequencies, it is recommended to perform the test during night-time or at low noise levels to minimize the effect of noises on accuracy. Photos of the tests under different noise levels are shown in Figure 11.  
The study also verified the effectiveness of the UAV-LDV system in identifying debonding damage to the HFSCGCW at noise exposure, and the results are shown in Figure 12. The research findings indicate that noise levels do affect the test results, as the outcomes at different noise levels vary significantly from those predicted by the numerical simulation. The results show that the damage detection capability of the UAV-LDV system is significantly affected when the noise levels are 20, 30, and 40 dB. The assessment diagrams do not accurately reflect the location and severity of the damage. This is attributed to the excitation energy level at this time, which is similar to that of the ambient noise, causing the energy level of the structure to fluctuate more and have a larger absolute value. As the  
Figure 11: Testing photographs under noises. (**a**) 1 m ranging fixed test under noises. (**b**) 1 m ranging mobile test under noises.