High-speed scanning chromatic confocal sensor for 3-D imaging with modeling-free learning control

Area of Science:

• Optical Engineering
• Surface Metrology

Background:

• Surface topography measurement is crucial for quality control and material science.
• Traditional scanning methods can be slow or require complex setups.

Purpose of the Study:

• To develop a high-speed, compact scanning system for surface topography measurement.
• To integrate an off-the-shelf chromatic confocal displacement sensor for enhanced reliability.

Main Methods:

• Integration of a galvanometer scanner to direct the optical point, avoiding sensor movement.
• Implementation of model-free learning for fast and accurate scanning motion control.
• Geometric model-based correction to compensate for image distortion.

Main Results:

• Achieved high-speed scanning of surface topography.
• Demonstrated accurate measurement through model-free learning and geometric correction.
• Successfully integrated a compact and reliable chromatic confocal displacement sensor.

Conclusions:

• The developed system offers an efficient and accurate solution for surface topography measurement.
• The integration of a galvanometer scanner and model-free learning significantly enhances scanning speed.
• Geometric correction ensures the precision of the topography data obtained.