Improving classification of spent refractory bricks

Analysis of spent brick using hyperspectral imaging

The EU-funded ReSoURCE project aims to increase the recovery of spent refractory bricks by sensor-based automated sorting. The project concentrates on spent bricks obtained from cement rotary kilns (CRK) and steel casting ladles (SCL) as feedstock. The developments in the project shall enable a fast and accurate sorting process to introduce recycled materials back into the production of new bricks without compromising on product quality.

A feasibility study done as part of the ReSource project, shows how hyperspectral imaging can help identify refractory bricks and classify them. The feasibility study was performed using HySpex hyperspectral cameras and the Prediktera Breeze software. Thanks to the extensive software/hardware integration it’s easy to create a fast and reliable analysis workflow. Combining high reliability with flexibility and ease-of-use, the Breeze software enables scientists to work both with data acquisition, exploratory analysis, modeling, real-time analysis and provides a clear path for transitioning to automated sorting solutions.

The Breeze software is using machine learning methods to classify brick samples.

Read the full application note here (HySpex website).

Funded by EU Horizon program and led by RHI Magnesita, the 4-year “Refractory Sorting Using Revolutionizing Classification Equipment” (ReSoURCE) project aims to ensure the green and digital transformation of the refractory recycling value chain.

The initiative will innovate the full process chain with an AI-supported multi sensor sorting equipment as its core technology. Combining laser-induced breakdown spectroscopy, hyperspectral imaging with optimised pre-processing and automated ejection will lay the foundation to set a new state of the art for refractory sorting starting of particle sizes down to below 1 mm.

Read more about the ReSoURCE project here.


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