Imec’s prototype hyperspectral camera can capture multiple types of data about materials or different parts of the same object. This could help in the development of automatic object classification systems that rival those used in state-of-the-art hyperspectral references and recorded spectra of plant material. The innovation could lead to small, cost-efficient cameras that can be adapted easily into vision systems.
The prototype chip's hyperspectral filter, which Imec developed, has 100 spectral bands between 560nm and 1,000nm. The filter bandwidth ranges from 3nm at 560nm to 20nm at 1,000nm, and the transmission efficiency is approximately 85 percent. Under illumination by a 450W halogen light, the prototype's typical image integration times are between 2 and 10 milliseconds.
Imec has been working on the development of a hyperspectral sensor for some time, based on its research reports from 2010 and 2009. Some of those efforts targeted machine vision, medical, and security applications.
The speed of Imec's demonstration system corresponds to an equivalent line speed of 2,000 lines per second -- much faster than current hyperspectral sensors. To adapt the technology to different industrial vision application requirements, a different commercially available or custom image sensor could be substituted with different pixel sizes and frame rates. The number of spectral bands and the spectral resolution of the hyperspectral filters can also be changed.
Having seen spectroscopy systems in the semiconductor industry in the 1980s, this seems like about as small a package as I can ever remember. Is this indeed smaller than the current state of the art? Has anyone else used a system on a chip approach like this one, Ann?
There's a large number of apps that could take advantage of this technology. Industrial machine vision and inspection of chips, boards and electronics sub-assemblies, R&D of several different kinds including component failure and analysis labs, medical labs of various kinds, and medical equipment manufacturing. It could possibly also be used in various kinds of materials detection, possibly in security apps, as well as for detecting counterfeit components made of inferior materials.
What I like most about this technology is the huge difference in size between other multispectral cameras I've written about in the past and the fact that this is a chip-level solution, even doing post-processing filters on-chip. I think the need for this technology will only continue to increase as design features keep getting smaller, and with the mixes of multiple material types.
This slideshow includes several versions of multi-materials machines, two different composites processes including one at microscale, and two vastly different metals processes. Potential game-changers down the line include three microscale processes.
UL is partnering with metals additive manufacturing (AM) supplier EOS to provide AM training to EOS's customers. It's designed to promote correct usage of AM technologies by OEMs and others in manufacturing.
To commemorate Earth Day, we take a look at the state of ocean plastic. If things don't change, by 2050 the oceans will contain more plastic than fish by weight. Here are the problems, as well as some solutions.
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