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Automatic optical structure optimization method of the laser triangulation ranging system under the Scheimpflug rule.

Zhuojiang Nan, Wei Tao, Hui Zhao

    Optics Express
    |October 12, 2022
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    Summary
    This summary is machine-generated.

    This study introduces an automatic method to optimize optical parameters for laser triangulation systems, reducing human error and improving measurement accuracy. The novel approach enhances system performance and efficiency compared to traditional methods.

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    Area of Science:

    • Optics
    • Metrology
    • Optical Engineering

    Background:

    • Accurate optical structure parameter design is crucial for laser triangulation ranging systems.
    • Current design processes rely on designer experience, introducing potential human errors and limiting measurement accuracy.
    • Automated optimization is needed to enhance precision and reliability in these systems.

    Purpose of the Study:

    • To propose and validate an automatic optimization method for optical structure parameters in laser triangulation ranging systems.
    • To improve measurement accuracy by minimizing human error in the design process.
    • To enhance the optical sensitivity and reduce nonlinearity of the system.

    Main Methods:

    • Constructed an optical sensitivity optimization model with boundary conditions for clear imaging and sensor dimensions.
    • Applied the Scheimpflug rule for clear laser imaging and constrained sensor geometry.
    • Developed a mutation operator-based particle swarm optimization (M-PSO) algorithm for parameter search.
    • Validated the method using ZEMAX simulations and an experimental platform.

    Main Results:

    • Achieved maximum optical sensitivity of 3.496 with optimal nonlinearity of 0.039% F.S.
    • Demonstrated significantly higher convergence efficiency compared to traditional Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods.
    • Successfully optimized optical parameters for three typical working distances and ranges.

    Conclusions:

    • The proposed automatic optimization method effectively improves measurement accuracy in laser triangulation systems.
    • M-PSO algorithm offers superior convergence efficiency over traditional optimization techniques.
    • This approach provides a robust and efficient solution for optical parameter design, reducing reliance on expert experience.