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Multi-Algorithm Collaborative Method for External Dimension Inspection of Engineering Vehicles
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DOI：10.3390/pr13123881.png)
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Abstract
En 中文
Aiming at the technical challenges of large dust interference, complex measurement parameters, and high real-time requirements in the automated sampling scenario of iron powder transportation vehicles, a method for external dimension detection that integrates laser radar and multi-algorithm collaboration is proposed. By improving ICP point cloud registration, Moving Least Squares surface reconstruction (MLS+), and Gaussian mixture model (GMM-EM) algorithms, the full process automation measurement of carriage length/width/height, top angle coordinates, and reinforcement positions is achieved. Experiments have shown that the system maintains a stable measurement error within +/- 5 cm and a single-frame processing time of <= 2.1 s in environments with PM2.5 <= 500 mu g/m3, providing an innovative solution for intelligent detection in industrial scenarios.
Keywords:
external dimensions
automatic measurement
laser radar
point cloud processing
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