Real-Time, Non-Contact Sorting of Plastics for Recycling Using Hyperspectral Imaging
This feasibility study utilized an inno-spec GmbH (now a Headwall Group company) hyperspectral imaging system consisting of a RedEye 1.7 (950 – 1700 nm) push-broom camera, compact scanning stage, tungsten halogen lighting, and a host computer running perClass Mira software. Plastic samples of known composition were scanned and a model created to show which samples were made of which polymer. Once properly trained, mixed batches of plastic were passed under the RedEye sensor, detected and false-colored using perClass Mira in real time! In a factory scenario, the positions of each plastic type is sent downstream.
Sorting Textiles for Recycling
Of the many efforts of conservation and reduction of waste, textiles remain one of the greatest challenges. The United States EPA estimates that of the 25 billion pounds of post-consumer textile waste recycled, only 15% is recycled and repurposed, while the remaining 85% of it ends up in landfills.1 The challenge facing textile recycling projects is discerning between similar looking fabrics at a high throughput. The ideal solution for this challenge would be a non-contact classifier that can sort the different fabrics and blends at high speeds. With Headwall’s hyperspectral imaging (HSI) sensors, and
perClass Mira’s machine learning software, Headwall provides a potential solution to this problem.