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Photodiode-based cutting interruption sensor for near-infrared lasers.

B Adelmann, M Schleier, B Neumeier

    Applied Optics
    |March 15, 2016
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    A new photodiode sensor system reliably detects cutting interruptions during fiber laser cutting. This system achieved 0% alpha and beta errors across various materials and thicknesses, offering significant industrial potential.

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    Area of Science:

    • Materials Science
    • Optical Engineering
    • Industrial Automation

    Background:

    • Laser cutting is a critical industrial process.
    • Detecting cutting interruptions is essential for quality control and efficiency.
    • Existing methods may lack robustness or versatility.

    Purpose of the Study:

    • To develop and validate a photodiode-based sensor system for real-time detection of cutting interruptions during fiber laser cutting.
    • To assess the system's performance across diverse materials, thicknesses, and cutting conditions.
    • To evaluate the system's potential for industrial implementation.

    Main Methods:

    • Utilized an InGaAs photodiode to capture thermal radiation from the laser cutting process zone.
    • Employed a ring mirror and optical filter arrangement for signal acquisition.
    • Digitalized the photodiode signal at 20 kHz and applied Chebyshev Type I filtering.
    • Established a threshold-based detection algorithm using piercing signals.

    Main Results:

    • Successfully detected 100% of cutting interruptions (83 cases) with zero false positives (266 cases).
    • Demonstrated effective detection across mild steel, stainless steel, and aluminum, with varying material thicknesses.
    • Confirmed applicability to both standard laser cutting and laser flame cutting processes.
    • Achieved an alpha error of 0% and a beta error of 0%.

    Conclusions:

    • The developed photodiode sensor system offers a highly accurate and reliable method for detecting cutting interruptions in laser cutting.
    • Its versatility across materials, thicknesses, and cutting types, coupled with easy integration, highlights its significant industrial applicability.
    • The system's high detection rate and low error rate promise enhanced quality control and reduced waste in manufacturing.