New Laser Technology in Non-contact Optical Dimensional Metrology

API’s Dynamic 9D LAser Detection And Ranging system (LADAR) captures both dimensional and surface geometry data. 9D LADAR incorporates a technology intended to revolutionize automated production measurements. The patent-pending Dynamic 9D LADAR offers an interferometry-based system by incorporating Optical Frequency Chirping Interferometry (OFCI) technology. API notes 9D LADAR is particularly useful in applications for the automated inspection of automotive and aerospace manufacturing and assembly.

9D LADAR’s data collection of production measurements seeks to represent the next generation of dimensional inspection solutions. API says this technology is meant to replace traditional, off-line, large volume coordinate measuring machines (CMM) and near-line and in-line inspection solutions by using both optical laser-line and structured light scanning sensors.

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The two-axis 9D LADAR system processes measured data at the rate of 20,000 points per second and with scanning speeds of 0.2 seconds/cm². Furthermore, 9D LADAR’s high-dynamic range is insensitive to target reflectivity, can measure translucent materials and is able to measure target features with up to an 85° incidence angle. High-density raster scanning delivers up to 50 lines per second with 0.1 mm line spacing. 9D LADAR’s on-board scale reference system delivers 2D and 3D accuracies of 6 µm/m, providing comparable accuracies to benchmark accuracy large volume CMMs, according to API.

Dynamic 9D LADAR’s compact design, weighing 10.4 kg, incorporates an integral controller with ethernet communication, enabling integration to both portal CMM frames or 6-axis industrial robots, including 7-axis rail-mounted configurations.

9D LADAR’s iVision smart camera system supplies instant part visualization for automated scan path planning, providing both automated feature and targeted region measurement and remote measurement operation viability.

API’s Dynamic 9D LADAR delivers X, Y, Z, I, J and K data for each generated cloud point along with the addition of R, G and B data, enabling for scanned data to be imaged directly onto the captured camera image. This capability displays characteristics with distinct background color contrast, surface vectors, surface roughness and more, which can be difficult to isolate with only the standard 3D point cloud data.