Optical measurement network for large-scale and shell-like objects.

Area of Science:

• Optics and Photonics
• Metrology
• Computer Vision

Background:

• Accurate 3D measurement of large-scale, complex objects like shells presents significant challenges.
• Existing optical methods often struggle with scale, object complexity, and achieving high precision.

Purpose of the Study:

• To propose and validate a novel optical measurement method for large-scale, shell-like objects.
• To develop a robust system for 3D reconstruction and comparison with design models.

Main Methods:

• A model-based optical measurement network utilizing multinode three-dimensional (3D) sensors.
• Synthetic calibration method for enabling accurate measurements.
• Phase-aided active stereoscopy applied to each sensor for partial range image acquisition.
• Registration of multiple range images to create a complete 3D model.

Main Results:

• Successful 3D reconstruction of large-scale, shell-like objects.
• Quantitative comparison between the reconstructed 3D model and the computer-aided design (CAD) model.
• Experimental validation confirming the accuracy and feasibility of the proposed optical measurement approach.

Conclusions:

• The proposed multinode 3D sensor network offers an effective solution for measuring large, shell-like objects.
• The synthetic calibration and phase-aided stereoscopy are key to achieving accurate 3D reconstructions.
• The method provides a reliable means for quality control and analysis by comparing real-world objects to their digital counterparts.