STTR Phase I: Reducing Mining Waste and Energy Using a Spectral Imaging Tracking System

Award Information
Agency:
National Science Foundation
Amount:
$225,000.00
Program:
STTR
Contract:
1332130
Solitcitation Year:
2013
Solicitation Number:
N/A
Branch:
N/A
Award Year:
2013
Phase:
Phase I
Agency Tracking Number:
1332130
Solicitation Topic Code:
AS
Small Business Information
SPLIT ENGINEERING LLC
2555 N. Jackrabbit Avenue, TUCSON, AZ, 85745-0000
Hubzone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Duns:
035909873
Principal Investigator
 Donald Kraemer
 (520) 327-3773
 dkraemer@spliteng.com
Business Contact
 Donald Kraemer
Phone: (520) 327-3773
Email: dkraemer@spliteng.com
Research Institution
 University of Arizona
 Kwangmin Kim
 Civil Engineering Bldg., #72
Tuscon, AZ, 85721-
 () -
 Nonprofit college or university
Abstract
This Small Business Technology Transfer Phase I project will involve the development of an innovative spectral image system to track rock material flows through mining operations. Accurately tracking material flows will allow smarter mineral processing circuits and optimized blasting, significantly reducing waste and energy. This addresses two of the central environmental impacts associated with mining: the size of the environmental footprint, and the large amount of energy used. The tracking system will be based on spectral imaging of the ore at various locations, such as after blasting, during the various stages of crushing and grinding, and before and after stockpiles and bins. The system will continuously track ore type at these locations, based on the unique spectral signature of different ore types in a mine. Accurate material tracking will be accomplished by integrating push-broom hyperspectral imaging with particle delineation algorithms, and by developing a tracking algorithm that tracks both rock type and material volumes. The Phase I work will involve spectral laboratory testing in simulated mining environments using mine rock samples, the development of algorithms to process the integrated spectral/particle delineation data, the development of a tracking algorithm, and the determination of optimal hardware and software for a prototype system. The broader impact/commercial potential of this project will be a reduction in the environmental impact of mineral operations and a reduction in energy consumption, via solutions applied during processing. The proposed technology presents new opportunities to improve mineral processing to customize the techniques to each specific rock type encountered. The tracking mechanisms for material types will enable operators to adjust settings for the ore type to effectively maximize the recovery while reducing unproductive activities. As a result, requirements for energy, materials, and solutions will be reduced throughout the process. The significant benefit achieved will be an overall reduced physical footprint of mining operations. This technology will also promote further investment into existing operations as opposed to the creation of new green-field projects. The new information and data provided by this system will allow more insight on the physical, mechanical and chemical properties that affect mineral extraction. This effort will in turn drive additional research by universities which will further understanding of the process and the advancement of the technology. Finally, the advancement of hyperspectral imaging technologies will cross-over to other applications and industries that will further research and investigation.

* information listed above is at the time of submission.

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