SBIR-STTR Award

Development of a full-scale reliability based Prognostic Health Management (PHM) models/algorithms that are based on the physics of failure and actual failure data (past experience, ground tests) and integrate them into real time software tool for the health monitoring of the satellite payload systems is proposed. The predictive prognostic models proposed for development shall utilize expert knowledge and experience to identify possible failure mechanisms, including past performance and test data, degradation modes, and effects of uncertainties in the involved variables. The Spacecraft Prognostic Health Management System (SPHMS) software tool shall be developed so that it is user friendly and can be easily interfaced with other tools of the spacecraft autonomy.  The proposed SPHMS shall be capable of assessing the payload performance reliability and/or the potential for near term failure as well as allow the identification of parameters governing the payload system performance. This will allow an informed decision to be made on payload performance reliability and effectiveness of target identification and tracking process.  Additionally, the proposed SPHMS will be developed in a generic manner so as to make it applicable to different types of satellite systems.

Benefit:
The ability to accurately identify the target and track its movement is primarily dependent on the payload performance of the satellite system.  Reliability based prognostic health management  lends significant benefits from the viewpoint of insuring that mission critical functions can be carried out with a high probability of success. In addition, the proposed evaluation system will allow identification of questionable components, subsystems and its operating characteristics in a logical manner based on a detailed physics-based understanding of the various failure modes and performance degradation mechanisms. This will allow an informed decision to be made on how to overcome the weakness of a degrading component/system by using the strength of healthy components/system and empower the satellite self awareness.  It also, enables making decisions on how reliable the target identification and tracking of the system is. Integrated physics-based upward compatible SPHMS provides easy integration in to the larger as well as a cluster of payload systems.  It enables the payload designer to use the optimum capability of each individual constituent component and determine the design payload for a desired reliability while reducing cost and increasing the confidence in the mission and objectives.

Keywords:
Satellite, Reliability, Prognostic, Performance, Failure, Degradation, Sensors, Sensitivity

Sest, Inc. has made significant progress during Phase I effort to perform feasibility study, conceptual development and modeling techniques for the development of a full-scale reliability based Spacecraft Prognostic Health Management System (SPHMS) based on the physics of failure, actual failure data (past experience, ground tests), real time performance data and integrate them into real time software tool for the health monitoring of generic satellite payload systems. The fully developed SPHMS during Phase II effort will: have predictive prognostic models combining the individual component/subsystem (such as electro optics, refrigeration and heat rejection system, gimbal, electronics, reaction wheels, etc.) and their interactions, identify degradation modes and possible failure mechanisms, and impact of uncertainties in the variables controlling the payload performance and reliability. The proposed SPHMS shall be fully capable of assessing the payload performance reliability, the potential for near term failure, predicting reliable remaining useful life and identify questionable component/subsystem operating characteristics in a logical physics-based manner based on a detailed understanding of the various failure modes / performance degradation mechanisms present. The proposed SPHMS will utilize data accumulated during the life, past performance test data of other similar spacecrafts and highly adaptable ground based simulation to achieve space situational awareness and mission success. This integrated package development will be such that it can be integrated in to a higher level complex system seamlessly.

Benefit:
The ability to accurately identify the target and track its movement in order to have situational awareness is primarily dependent on the payload performance of the satellite system. Reliability based prognostic health management lends significant benefits from the viewpoint of insuring that mission critical functions can be carried out with a high probability of success. In addition, the proposed evaluation system will allow identification of questionable components, subsystems and its operating characteristics in a logical manner based on a detailed physics-based understanding of various failure modes and performance degradation mechanisms. This will allow an informed decision to be made on how to overcome the weakness of a degrading component/system by using the strength of healthy components/system and empower the satellite self awareness. It also, enables making decisions on how reliable the target identification and tracking of the system is. Integrated physics-based upward compatible SPHMS provides easy integration in to the larger as well as a cluster or constellation of payload systems (distributed network sensing). It enables the payload designer to use the optimum capability of each individual constituent component and determine the design payload for a desired reliability. The above will lead to a minimization in the number missions that must be terminated due to failure of the critical component, along with managing the resources in a cost effective manner. Over and above this, the cost of all the desired and designed missions shall be reduced due to (i) knowledge of degradation mechanisms, (ii) optimally using the component and subsystem’s reliable capacity, (iii) reduction in payload system design and hardware cost as well as training costs, (iv) reduction in rates of false identification and tracking and thereby achieving high performance reliability, (v) safely decommissioning the mission. Overall the greatest benefit will be the confidence in the missions and targeted objectives.

Keywords:
Satellite, Reliability, Prognostic, Performance, Failure, Degradation, Sensors, Sensitivity