Diagnostics and Health Management for Remotely Piloted Aircraft (RPA) Payloads

Award Information
Department of Defense
Air Force
Award Year:
Phase II
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
Solicitation Number:
Small Business Information
QorTek, Inc.
1965 Lycoming Creek Road, Suite 205, Williamsport, PA, -
Hubzone Owned:
Minority Owned:
Woman Owned:
Principal Investigator:
Gregory Bower
Principal Investigator
(570) 322-2700
Business Contact:
Cathy Brooke
Chief Financial Officer
(570) 322-2700
Research Institution:
ABSTRACT: Advantages of health management algorithms to critical and complex systems are numerous. For example, a health management system can improve system readiness by quantifying the health of the system and reduce maintenance costs. By applying these methodologies to unmanned vehicle payloads, the same benefits can be obtained. In this proposal, QorTek is teaming with KEYW to apply a health management methodology to synthetic aperture radar (SAR) payloads. The health methodology is based on symbolic dynamics, a statistical pattern recognition tool. This methodology enables health monitoring of the complex SAR payload and will also be able to predict remaining life. A problem with these methodologies is to discriminate differences in the payload as a result of operational characteristics and internal degradation. It is advantageous to determine if payload degradation is due to internal effects such as from wear-out or if degradation is due to outside effects such as those derived from Electronic Warfare (EW) events (jamming). The methodology will be developed to handle both of these situations. The algorithm will be further tested on a flight platform and verified. Health monitoring capabilities will also be expanded through research and development in this proposal to both infrared (IR) and electro-optical (EO) payloads. BENEFIT: By implementing a health management methodology, maintenance costs for complex systems such as a SAR payload can be reduced. Maintenance can be scheduled as necessitated by the payload versus by use as required in current systems. In addition, the statistical algorithm lends itself well to expanding the methodology into additional payloads such as EO and IR. This will enable a complete health management tool that can monitor the critical payloads on military ISR vehicles. In addition, the maturation of the algorithm will enable future deployments in the commercial sector such as in airlines. Additionally, another commercial application is within the traction community monitoring the health of the electronic equipment. Industrial applications can also be targeted through monitoring numerous electronics and machines.

* information listed above is at the time of submission.

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