From optics and lighting to smart cameras to artificial intelligence (AI) and machine learning (ML), machine vision is growing in industrial automation and changing in many ways. Four innovations are highlighted.
Machine vision systems have moved beyond elevated sensors to inspection integrated in controllers. Choosing the right based PC-based automation platform can make them even better.
MIT researchers have found similarities between how some computer-vision systems process images and how humans see out of the corners of their eyes.
CoaXPress 2.0 (CXP 2.0) and 10GigE Vision (10 GigE) are the two most popular interfaces for machine vision and discrete sensors; CXP 2.0 has advantages in flexibility, speed, bandwidth and cable length.
An ultra-compact angle sensor built from flat optics captures these measurements at 30 frames per second, which will allow for more accurate and precise measurements of tiny atomic materials.
Manufacturers can benefit from AI machine vision technologies by increasing uptime, leverage preventive maintenance and more.
Vibration analysis allows early detection of wear, fatigue and failure in rotating machinery because vibration occurs in all rotational assets, but generally highlights an issue discovered by higher readings and particular frequencies.
A smart material-sensing platform for laser cutters that can differentiate between 30 materials commonly found in makerspaces and workshops has been developed by MIT researchers. See video demonstration.
A new record for the temperature at which materials have superconductivity and has developed a novel way to synthesize superconducting materials at lower pressures than previously reported. See video.
The Ohio State University researchers developed a design for absorbing vibrations that could help create better soundproof walls, make vehicles more streamlined and help in other engineering aspects.