SBIR/STTR Research Award

Computerized system for predicting noise emission from mining machines

Award identifier 057bbfa92c37e1222b675693fbd66cbc89a4b38b101e27a2f1d9021f0e6009dbAwarding agency Department of Health and Human Services · Centers for Disease Control and Prevention

Award amount

$150,000

Program and phase

SBIR · Phase I

Award year

2016

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Award details

Awarding agency
Department of Health and Human Services
Branch
Centers for Disease Control and Prevention
Recipient company
TRIBO FLOW SEPARATIONS, LLC
Proposal award date
2016-09-01
Contract end date
2017-02-28
UEI
UFCJJCJ8KKJ3
Solicitation number
PA15-269
Topic code
NIOSH

Research abstract

The control or mitigation of equipment noise is paramount for worker protection in mines If a computerized system was developed that accurately predicted noise emission during equipment design and siting the current need to build site and then operate equipment to understand or control its noise emission would be eliminated This project aims to develop such a computerized system With success it would improve timelines for developing and implementing worker protection devices and protocols decrease substantially the amount of time and costs associated with noise emission measurements and control practices provide greater worker safety in all industrial activities and lead to the use of predictive noise analyses for equipment that is to be used in all industrial residential and commercial buildings The goals of the project are to develop techniques and algorithms for predicting noise sound pressure from mining equipment during the design and siting process and show the feasibility of a computerized system for predicting worker noise exposure from mining equipment noise emissions These goals are attained through comprehensive noise emission tests and simulations that include cooperative research between Tribo Flow Separations and the University of Kentucky and interactions with personnel and assessments of mining equipment at the Pittsburgh Office of Mine Safety and Health Research The long term objectives include establishing the scientific basis for reliable boundary element method and sub structured boundary element method simulations for determining noise transfer functions refining the applicability of patch contribution analysis on scale models of equipment and on operating equipment developing reliable specifications for computer algorithms useful for defining noise emission during equipment design and siting and initiate interactions with a mining equipment manufacturer to prepare for demonstration and commercialization of the computerized system With success in the research it is expected that predictions of worker noise exposure before machinery is placed in operation will be possible thereby enabling noise mitigation procedures and noise protection protocols to be put into effect before a machine is turned on This computerized system will promote worker safety while decreasing the extent of worker injuries and illnesses caused by vibration and noise The research focuses on developing a computerized system which can predict noise levels from large machinery during design and planned siting within mining operations With success predictions could be made of worker noise exposure before machinery is placed in operation thereby enabling noise mitigation procedures and noise protection protocols to be put into effect before a machine is turned on This system will promote worker safety while decreasing the extent of worker injuries and illnesses caused by vibration and noise

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

6 SBIR/STTR records share this UEI (2004–2020). Reported award amounts total $1,086,885. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: National Science Foundation, Department of Health and Human Services, National Aeronautics and Space Administration

Agency intelligence

Department of Health and Human Services

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