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Sterling, VA, United States

Grant
Agency: Department of Defense | Branch: Navy | Program: STTR | Phase: Phase II | Award Amount: 1.59M | Year: 2008

Based on the research and analysis conducted during Phase I, it was determined that it is feasible to detect, diagnose, predict and manage impending failures in a rotating electrical machine (e.g., aircraft generator) using a real-time, sensory-updating residual life distribution estimation technique. Furthermore, the methodology allows us to develop a prognostic capability for the electrical power system components without the great expense of running components to failure. That is, the degradation based prognostic technique is an efficient way to develop predictive models in the absence of a prior sample of degradation signals. This is one of the most significant breakthroughs of this research effort. The feasibility was demonstrated analytically and through an experimental setup (rotating machine) in order to (a) test the alternative of using only in-service failure time data to evaluate the distribution of the stochastic parameters of the degradation model and (b) test a hypothesis about the functional form that a component’s degradation signal will follow, in the absence of a database of degradation signals.


Grant
Agency: Department of Defense | Branch: Navy | Program: SBIR | Phase: Phase I | Award Amount: 79.58K | Year: 2014

Prognostics and health management (PHM) technology is critical for monitoring, detecting, and managing impending faults and enabling proactive maintenance of electronic systems before actual failures occur. This is essential to enhancing weapons systems reliability and maintaining a high level of mission readiness and affordability. Current PHM advancements have focused on developing physics based and data driven models to enable the predictive capability. There is a need to integrate these advancements with Automatic Test Equipment data. This effort investigates the development and application of a toolset to enable the integration of data produced by the electronic system (BIT, on-system diagnostics) with data produced by health assessment models and algorithms and data from ATE test results- for system-level prognostics and health management of electronic systems. The effort researches and characterizes a systematic framework for the integration, processing, distribution and management of health state data across multiple networked ATE systems and multiple maintenance organizations. This effort includes investigating the application and enhancement of the latest IEEE ATS-related standards such as ATML to provide a structure for capturing, exchange and management of health state data and information across the maintenance infrastructure. A proof-of-concept demonstration for a small target system is part of this effort.


Grant
Agency: Department of Defense | Branch: Navy | Program: SBIR | Phase: Phase II | Award Amount: 652.38K | Year: 2015

Prognostics and health management (PHM) technology is critical for monitoring, detecting, and managing impending faults and enabling proactive maintenance of electronic systems before actual failures occur. This is essential to enhancing weapons system availability and maintaining a high level of mission readiness and system affordability. Current PHM advancements have focused on developing physics based and parametric data driven models to enable a predictive analytics capability. There is a need to integrate these advancements with Automatic Test Equipment data. This effort covers the development and application of a toolset to enable the integration of data produced by the electronic system (BIT, on-system diagnostics) with data produced by health assessment models and algorithms and data from ATE test results- for system-level prognostics and health management of electronic systems. The effort is focused on developing a system health record (SHR) framework for the collection, integration, processing, distribution and management of health state data across multiple networked ATE systems and multiple maintenance organizations. This effort includes the application and enhancement of the latest IEEE ATS-related standards such as ATML to provide a structure for capturing, exchange and management of health state data and information across the maintenance infrastructure.


Patent
Global Strategic Solutions LLC | Date: 2012-06-04

A system and method for suppressing radio frequency (RF) transmissions includes a transmitter for transmitting electronic signals that suppresses (e.g., prevents, disrupts, jams, interferes with or otherwise disables) RF transmissions. Some embodiments of the invention include a transmitter that suppresses one or more signals transmitted from a target transmitter in an RF transmission system to a target receiver in a wireless device operating in the RF transmission system to prevent, disrupt, jam, interfere with or otherwise disable an RF transmission between the target transmitter and the target receiver in the wireless device (i.e., target wireless device). These systems and methods may be used to interrupt communication, command and control of non-friendly combatant. These systems and methods may also be used to suppress RF transmissions to prevent the detonation of improvised explosive devices, or IEDs.


Grant
Agency: Department of Defense | Branch: Navy | Program: STTR | Phase: Phase I | Award Amount: 69.46K | Year: 2010

Prognostics and health management (PHM) systems are critical for detecting impending faults and enabling a proactive decision process for maintenance or replacement of avionics systems before actual failures occur. A PHM system is essential to enhancing aircraft systems reliability and maintaining a high level of mission readiness and affordability. Current PHM advancements are focused on aircraft structures and electro-mechanical components. There is a need to address the unique PHM system-level design characteristics for avionics systems. This effort investigates the development of a toolset to enable the integration of data, models and algorithms for system-level prognostics and health management of avionics systems. The effort researches and characterizes a systematic framework for the integration, processing, and distribution of health state data from onboard monitoring systems to off-board Automatic Test Systems (ATS). This includes investigating the application of the latest Condition Based Maintenance (OSA-CBM), MIMOSA, ISO and IEEE ATS-related standards to provide a standard, common model (structure) for exchange of health state data and information across the maintenance infrastructure. Including assessment of data analysis and modeling techniques to enable system-level health assessment and performance life remaining predictions. A technology development plan and a desktop proof-ofconcept demonstration for a small target system are part of this effort.

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