An Assessment Methodology to Evaluate In-Flight Engine Health Management Effectiveness

Statistics – Methodology

Scientific paper

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Scientific paper

flight effectiveness of candidate engine health management system concepts. A next generation engine health management system will be required to be both reliable and robust in terms of anomaly detection capability. The system must be able to operate successfully in the hostile, high-stress engine system environment. This implies that its system components, such as the instrumentation, process and control, and vehicle interface and support subsystems, must be highly reliable. Additionally, the system must be able to address a vast range of possible engine operation anomalies through a host of different types of measurements supported by a fast algorithm/architecture processing capability that can identify "true" (real) engine operation anomalies. False anomaly condition reports for such a system must be essentially eliminated. The accuracy of identifying only real anomaly conditions has been an issue with the Space Shuttle Main Engine (SSME) in the past. Much improvement in many of the technologies to address these areas is required. The objectives of this study were to identify and demonstrate a consistent assessment methodology that can evaluate the capability of next generation engine health management system concepts to respond in a correct, timely manner to alleviate an operational engine anomaly condition during flight. Science Applications International Corporation (SAIC), with support from NASA Marshall Space Flight Center, identified a probabilistic modeling approach to assess engine health management system concept effectiveness using a deterministic anomaly-time event assessment modeling approach that can be applied in the engine preliminary design stage of development to assess engine health management system concept effectiveness. Much discussion in this paper focuses on the formulation and application approach in performing this assessment. This includes detailed discussion of key modeling assumptions, the overall assessment methodology approach identified, and the identification of key supporting engine health management system concept design/operation and fault mode information required to utilize this methodology. At the paper's conclusion, discussion focuses on a demonstration benchmark study that applied this methodology to the current SSME health management system. A summary of study results and lessons learned are provided. Recommendations for future work in this area are also identified at the conclusion of the paper. * Please direct all correspondence/communication pertaining to this paper to Dennis G. Pelaccio, Science

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