Development of View Optimization Techniques for Structural Monitoring Systems Using Post-Processing of Structural Analysis and Image Processing
This study aimed to enhance the efficiency of monitoring systems for structures undergoing continuous deformation by integrating structural analysis and image processing techniques. It addresses the challenge of optimizing real-time structural monitoring for precise deformation visualization, critic...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10819407/ |
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| Summary: | This study aimed to enhance the efficiency of monitoring systems for structures undergoing continuous deformation by integrating structural analysis and image processing techniques. It addresses the challenge of optimizing real-time structural monitoring for precise deformation visualization, critical for engineering applications. The proposed framework for view optimization utilized the results from structural analysis performed in ABAQUS to extract initial camera positions and direction vectors, which served as inputs for an optimization algorithm. The optimization process applied image processing methods to detect deformation areas, while performance was evaluated at each iteration and saved when improvements were found. Camera parameters were iteratively updated using gradient descent and adjusted learning rates to ensure effective visualization of deformation. Experimental results confirm that this approach not only visualizes structural analysis outcomes effectively but also optimizes camera views for tailored monitoring systems. This integrated approach significantly enhances real-time monitoring, making it suitable for infrastructure health monitoring, civil engineering, and mechanical systems analysis. Overall, this work demonstrates the feasibility of combining structural analysis with imaging techniques for more accurate and efficient monitoring solutions. |
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| ISSN: | 2169-3536 |