# Vision-Based Damage Detection Method Using Multi-Scale Local Information Entropy and Data Fusion
## 5 Conclusions  
This study proposes a novel vision-based method for damage detection using multi-scale local information entropy and data fusion. We utilize an advanced phase-based optical flow algorithm to acquire high-spatial-resolution vibration signals. The damage location is precisely determined through the fusion of damage information extracted by the proposed MS-LIE across all scales. A series of numerical and experimental scenarios are designed to validate the method. According to the results of investigations, the following conclusions can be drawn:  
1. The vibration signals obtained by phase-based optical flow estimation show good agreement with those from the laser vibrometer and FEM in terms of displacement, frequency, and mode shapes. This indicates that the vision-based method can deliver precise vibration measurements obviating the need for speckle patterns or high-contrast markers on the surface, and the high-spatial-resolution mode shapes provided by the vision-based method are reliable. The utilization of the phase-based optical flow estimation technique facilitates the implementation of a non-contact, non-destructive monitoring approach that can be applied to a diverse range of structures.
2. The novel damage index MS-LIE integrates the multi-scale analysis component and the entropy analysis component, addressing both the issue of detection sensitivity and noise immunity, thereby showcasing enhanced performance. The MS-LIE effectively reveals damage features in Gaussian multi-scale space, even in the presence of noise. Benefiting from utilizing damage evidence across all scales through data fusion technique, the proposed method demonstrates robustness in detecting damage under various noisy environments. The final damage probability distributions accurately  
Figure 26: The damage localization results of multiple damages: (**a**) based on the 1 st mode shape, (**b**) based on the 2 nd mode shape, (**c**) based on the 3 rd mode shape.  
identify instances of single and multiple damages without the necessity of a baseline data set as a reference.
3. The results of the ablation study have demonstrated the utility of entropy-based and multi-scale analysis-based approaches in SHM. It can inform future research by encouraging the exploration of other entropy measures for damage detection and promoting the integration of advanced multi-scale analysis-based data fusion techniques to further enhance detection capabilities.  
Despite the laboratory success of this paper, there are some noteworthy limitations. On the one hand, vision-based measurements for large structures may suffer from the problem that the imaging area does not fully cover the structure. This needs to be solved by introducing partition measurements and mode shape splicing techniques. On the other hand, the structural geometrical complexity of the structure may cause overlap or obstruction problems in the imaging area. This needs to be addressed by further multi-camera measurements. Future work will aim to overcome these limitations and further verify the generalizability to more complex structures such as bridges, towers, or composite materials. Additionally, we will explore quantifying the sensitivity of key parameters for different systems and structural conditions.  
Methodology and validation and formal analysis and writing--original draft preparation, Y.Z.; writing--review and editing and supervision and funding acquisition Z.X.; software and data curation, G.L.; conceptualization, C.X. All authors have read and agreed to the published version of the manuscript. This work is supported by the Basic Research Project Group (No. 514010106-302).  
Not applicable.  
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.  
The authors declare no conflicts of interest.