研究目的
To compare the performance of digital image analysis and three-dimensional scanning techniques for detecting shape modifications in a morphing blade equipped with shape memory alloy strips under thermal activation.
研究成果
Digital image analysis provides accurate 2D shape detection when properly aligned, with deviations less than 0.5 mm. 3D scanning with Kinect sensors offers comprehensive shape detection but with higher deviations up to 3 mm. Both methods are feasible for non-contact measurement of morphing structures, enabling virtual model creation for further analyses.
研究不足
The accuracy of digital image analysis is limited by camera resolution and alignment, with deviations up to 0.7 mm. 3D scanning with Kinect sensors has deviations up to 3 mm, especially at edges due to reflection issues. The methods require proper setup and are sensitive to environmental factors like light and angle.
1：Experimental Design and Method Selection:
The study employs digital image analysis using cameras and 3D scanning using Kinect sensors to detect shape changes in a morphing blade. The blade is activated thermally in a wind tunnel, and non-contact optical methods are used for measurement.
2：Sample Selection and Data Sources:
A morphing blade made of a polymeric matrix with embedded SMA strips is used. Data is acquired from cameras and Kinect sensors during heating and cooling ramps.
3：List of Experimental Equipment and Materials:
Equipment includes digital cameras, Kinect I and II sensors, a purpose-built wind tunnel (SBTF), thermocouples, anti-glare spray, and software tools like MeshLab, Blender, and CloudCompare. Materials include the morphing blade, SMA strips, and polymeric matrix.
4：Experimental Procedures and Operational Workflow:
The blade is placed in the wind tunnel, and thermal activation is performed. Cameras record videos at 30 fps, and Kinect sensors capture point clouds every 15 seconds. Data is post-processed for 2D and 3D reconstruction.
5：Data Analysis Methods:
Digital images are analyzed for displacement vectors and 2D CAD reconstruction. Point clouds from Kinect sensors are filtered, meshed, and converted to CAD models using interpolation and solid modeling software.
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Kinect I
Kinect I
Microsoft
3D scanning and depth sensing for detecting blade shape modifications
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Kinect II
Kinect II
Microsoft
3D scanning and depth sensing with improved accuracy for detecting blade shape modifications
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Digital Camera
Recording videos for digital image analysis of blade shape
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Romer Laser Scanner
Romer
Reference 3D scanning for non-activated blade shape
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Thermocouple
K-type
Temperature measurement during activation tests
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Anti-glare Spray
Coating blade surface to reduce reflections for better scanning
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SDK Software Development Kit
Microsoft
Configuring Kinect sensors for data acquisition
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MeshLab
Open-source software for point cloud processing
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Blender
Open-source software for 3D modeling and mesh processing
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CloudCompare
Open-source software for point cloud comparison and analysis
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Polyworks V12
V12
Polyworks
Software for interpolating point clouds from laser scanner to create reference 3D shapes
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