SBIR/STTR Research Award

An Affordable Health and Usage Monitoring System (HUMS) for UAVs

Award identifier c73ad13f39deb32580a3060d2206fff8d20a748afd1711607d0a5b9b3730b4dcAwarding agency Department of Defense · Army

Award amount

$119,737

Program and phase

SBIR · Phase I

Award year

2004

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Award details

Awarding agency
Department of Defense
Branch
Army
Recipient company
Impact Technologies
Proposal award date
2003-12-04
Contract end date
2004-06-03
UEI
T1JNUWJLN5M1
Solicitation number
2003.2
Topic code
A03-074

Research abstract

Impact Technologies, in collaboration with Lord Corporation and the Georgia Institute of Technology, propose to develop an affordable/miniaturized health and usage monitoring system (HUMS) for unmanned aerial vehicles (UAVs). Based upon the unique requirements of UAVs, an innovative hardware/software solution will be developed and demonstrated that includes embedding advanced vehicle health management algorithms for anomaly detection, fault classification and prediction into a low-cost, aerospace-certified digital signal processing (DSP) based hardware platform. All critical parameters related to UAV performance and mechanical health will be monitored including aero-thermal flight parameters, propulsion system information, structural/vibrations and vehicle subsystem performance data to address condition-based maintenance activities that are required to ensure UAV mission success. Key UAV subsystems including the gas turbine engine, drive train (shaft/clutch), fan, louvers, actuators (fight control) and avionics will be monitored by the proposed system. The proposed UAV-HUMS will continuously assess and track the health of all critical UAV subsystems using a combination of anomaly detection and diagnostic reasoning software that can communicate the health status of the vehicle through a low-bandwidth air-to-ground link. The anomaly detection software will implement proven signal processing and automatic signal feature extraction techniques that are capable of identifying abnormal system behavior and reporting it to the diagnostic reasoning software. The diagnostic reasoning modules will utilize a combination of fuzzy reasoning and robust fault classifiers such as neural networks and support vector machines to obtain the fault diagnosis of the UAV. The development and integration of advanced diagnostic and prognostic algorithms into a real-time health monitoring system is expected to improve UAV mission success rates and positively impact total ownership costs. The proposed Phase I development includes a hardware/software demonstration of the next generation UAV-HUMS including embedded anomaly detection and diagnostic reasoning algorithms, DSP hardware specification and an on-board/off-board design trade study. This work will leverage Impact's existing expertise in air vehicle prognostic health management systems, Lord's expertise in flight-qualified electronics hardware and Georgia Tech's helicopter UAV test bed.

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

232 SBIR/STTR records share this UEI (1999–2014). Reported award amounts total $76,299,884. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Energy, Department of Homeland Security, Department of Transportation

Agency intelligence

Department of Defense

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