Multi-dimensional information sensing of complex surfaces based on fringe projection profilometry

Area of Science:

• Optical Metrology
• Surface Analysis
• Mechanical Engineering

Background:

• Accurate sensing of complex surface profiles is crucial for structural investigation and mechanical analysis.
• Current methods often require separate technologies, limiting comprehensive data acquisition.
• Fringe projection profilometry (FPP) excels at shape measurement but struggles with deformation and strain analysis due to tracking limitations.

Purpose of the Study:

• To develop a multi-dimensional information sensing method integrating digital image correlation (DIC) with FPP.
• To overcome the limitations of traditional FPP in analyzing deformation and strain.
• To achieve simultaneous high-resolution sensing of texture, shape, and mechanical parameters.

Main Methods:

• Introduction of colorful fluorescent markers for modulated information with high reflectivity and color difference.
• Development of a general information separation method to acquire texture, fringe patterns, and speckle patterns simultaneously.
• Integration of DIC techniques with FPP for enhanced data processing.

Main Results:

• Simultaneous acquisition of speckle-free 2D texture, 4D shape (x, y, z, t), and mechanical parameters (deformation, strain) for the first time.
• Demonstrated ability to measure and analyze 3D geometry and mechanical states of complex surfaces.
• Expansion of FPP capabilities without requiring additional hardware.

Conclusions:

• The proposed DIC-assisted FPP method offers a unified approach for multi-dimensional surface information sensing.
• This technique enhances the analytical capabilities of FPP systems for complex surface characterization.
• The method provides a cost-effective solution for advanced surface analysis and mechanical property evaluation.