SBIR/STTR Research Award

intelligent Frequency Modulated Continuous Wave (iFMCW)

Award identifier 67be754dcf0f92cac8feaf6e6c58a1823730a34a2996539be18ef7dca78b86a2Awarding agency Department of Defense · Army

Award amount

$173,000

Program and phase

STTR · Phase I

Award year

2022

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Award details

Awarding agency
Department of Defense
Branch
Army
Recipient company
AVNIK DEFENSE SOLUTIONS INC
Proposal award date
2022-06-16
Contract end date
2023-02-14
UEI
MJJUNNW1FKT4
Solicitation number
21.C
Topic code
A21C-T013

Research abstract

Operational availability, reliability, and performance of Army weapons systems platforms are key factors in achieving mission success. Aircraft, RADAR, intermediate Missile, and combat vehicles depend on the health of their systems to perform reliably over extended periods of time.  Maintenance of equipment and components, including interconnect cables and connectors, is an important aspect of reliability, assuring that weapons systems will operate properly when called upon.  Army maintainers and depot artisans have a requirement for an intelligent toolset to quickly detect, locate, characterize/classify, and predict wire and connector faults.  AVNIK Defense Solutions, Inc. (AVNIK) proposes an intelligent Frequency Modulated Continuous Wave (iFMCW) hand-held toolset for detection and diagnosis of faults in interconnect cables. We will work with our expert subcontractor research institution (RI) Auburn University and consultant subject matter experts (SMEs) at The University of Alabama at Huntsville (UAH) and Instrumental Sciences, Inc. (ISI).  We will research cable properties and iFMCW waveform options, apply data analytics methods to field data to characterize cable fault types, and demonstrate key elements of the toolset in the laboratory. Primary objectives of the Phase I research are to (1) evaluate efficacy of candidate iFMCW waveform parameters to determine locations and types of faults in cables, (2) determine the feasibility of applying data analytics and artificial intelligence techniques to field data sets to identify and quantify cable and connector fault characteristics, and (3) develop statistical methods to operate on toolset outputs to maximize fault detection/prediction accuracy.

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

8 SBIR/STTR records share this UEI (2017–2023). Reported award amounts total $4,718,579. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense

Agency intelligence

Department of Defense

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