Forskningsradar
← Tech & AI
Tech & AI 5.1

New camera-based tool detects machining flaws in real time without stopping production

Researchers have developed a non-invasive optical inspection system that uses standard camera images to assess machine tool performance and surface quality during production. The method matches theoretical precision within 1.85%, enabling manufacturers to catch defects immediately and reduce costly scrap—a significant advantage for high-volume precision manufacturing.

Originaltitel: In situ- On Machine - Post Process Metrology System Design for Machining System Characterization

Abstrakt

<p>The evaluation of machine tool characteristics and their impact on surface quality is challenging, often requiring disruptive traditional methods. This study introduces a novel, non-invasive approach using optical camera images for rapid and accurate assessment. Data robustness was ensured by acquiring initial images outside the machining chamber with consistent external illumination, focusing on detailed intensity profile analysis. Machined surfaces were processed using intensity profile extraction and Fast Fourier Transform (FFT). The dominant spatial wavelength (0.1833 mm) consistently showed excellent agreement (within 1.85%) with the theoretical feed per revolution (0.1800 mm). This robustly validates the method's ability to precisely capture primary kinematic tool marks. Temporal information, inferred from spatial frequencies, underwent subsequent FFT to identify periodic phenomena and harmonics. The comprehensive spatial and temporal FFT analyses offer detailed, quantitative surface characterizations. The clear distinctions in temporal harmonic patterns provide robust, frequency-domain signatures informing machining system performance and process integrity.</p>

Generera ett redaktionellt utkast på svenska