3D error calibration of spatial spots based on dual position-sensitive detectors

Area of Science:

• Optoelectronics
• Machine Vision
• Metrology

Background:

• Traditional CCD cameras have limitations in precise spatial light point detection.
• Position-Sensitive Detectors (PSDs) offer an alternative for optical measurement.
• Accurate 3D positioning is crucial in various scientific and industrial applications.

Purpose of the Study:

• To develop and validate a dual PSD vision system for 3D light point position detection.
• To investigate the impact of light spot size on positioning accuracy.
• To implement a nonlinear error calibration method for PSD measurements.

Main Methods:

• Utilized a dual position-sensitive detector (PSD) camera system.
• Derived a positioning model for 2D PSDs using Lucovsky's differential equation.
• Applied a particle swarm optimization combined with a back propagation neural network for nonlinear error calibration.
• Experimentally validated the system with a red LED light spot.

Main Results:

• The dual PSD system accurately determines 3D light point positions.
• Positioning accuracy is inversely proportional to the light spot size; smaller spots yield higher accuracy.
• The proposed calibration method effectively corrects nonlinear distortions in PSD measurements.
• The system demonstrates fast, reliable, and easy implementation for close-range measurements.

Conclusions:

• The dual PSD vision system provides an effective solution for spatial light point detection, especially under close-range conditions.
• Optimizing light spot size is key to improving the accuracy of PSD-based measurements.
• This method offers a robust approach for tracking the motion trajectory of light spots in space.