# Estimation of Wind Turbine Blade Icing Volume Based on Binocular Vision
## 5 Discussion  
Despite these promising results, several challenges remain. The accuracy of the proposed method in handling complex ice geometries requires further improvement, particularly under extreme weather conditions. Environmental factors such as fog, high humidity, temperature fluctuations, and the presence of dust particles can significantly  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**No** & **Volume (mm\({}^{3}\))** & **Measured Volume (mm\({}^{3}\))** & **Error (\%)** \\ \hline
1 & 97,608.69 & 92,667.37 & 5.06\% \\
2 & 197,717.39 & 184,961.32 & 6.45\% \\
3 & 257,391.30 & 232,847.36 & 9.54\% \\ \hline \hline \end{tabular}
\end{table}
Table 6: Volume measurement results and errors.  
Figure 11: Experimental results. (**a1–a3**) Photographs of the physical objects on the left; (**b1–b3**) disparity maps; (**c1–c3**) point cloud diagrams.  
degrade image quality by affecting light transmission and contrast, introducing noise into the stereo images and making it challenging for the algorithm to maintain high precision. Furthermore, offshore and onshore wind farms present distinct operational challenges and algorithmic applications. Offshore wind farms often face harsher conditions, including high humidity, salt spray, and stronger winds, which can further compromise image quality and sensor performance. Additionally, the deployment and maintenance of monitoring systems in offshore environments are more complex and costly than those onshore, potentially leading to differences in the accuracy and practicality of the proposed method that require further investigation.  
To address these challenges, future research should focus on optimizing the algorithm for real-time performance, enhancing robustness under varying environmental conditions. Fixed cameras installed on land could serve as a continuous monitoring tool for detectingicing and other damages, such as cracks or surface wear, while drones offer a flexible solution for inspections, especially during icing-prone seasons, though their deployment frequency and effectiveness depend on operational needs and weather conditions. Broader applications, such as monitoring ice on power lines, aircraft wings, and offshore platforms, should also be explored. Addressing these challenges will help transform the proposed method into a comprehensive and practical solution, ensuring the operational efficiency and safety of wind turbines in diverse and challenging environments.  
Conceptualization, F.W.; methodology, F.W.; software, Z.G.; validation, Z.G. and W.Q.; formal analysis, Z.G.; investigation, Z.G. and W.Q.; resources, Q.H.; data curation, F.W.; writing--original draft preparation, F.W.; writing--review and editing, Q.H.; visualization, W.Q.; supervision, Q.H.; project administration, Q.H.; funding acquisition, Q.H. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Inner Mongolia Natural Science Foundation grant number 2022 MS050500; this research was funded by the Inner Mongolia Autonomous Region Science and Technology Project for Application and Development grant number 2020 GG0314.  
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The authors declare no conflicts of interest.The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.