Abort Trigger False Positive and False Negative Analysis Methodology for Threshold-based Abort Detection

Kevin J. Melcher, Jose A. Cruz, Stephen B. Johnson, and Yunnhon Lo
Submission Type: 
Full Paper
Supporting Agencies (optional): 
NASA
AttachmentSizeTimestamp
phmc_15_070.pdf776.09 KBOctober 21, 2015 - 7:02am

This paper describes a quantitative methodology for bounding the False Positive (FP) and False Negative (FN) probabilities of a human-rated launch vehicle (LV) abort trigger (AT) that includes logic for Sensor Data Qualification (SDQ). In this context, an AT is a specific type of failure detection mechanism, while SDQ is a mechanism for identifying corrupt sensor data before it is used by the AT. The FP/FN methodology presented here was developed to support estimation of the probability of Loss of Crew (LOC) and Loss of Mission (LOM) for the Space Launch System (SLS) which is being developed by the United States National Aeronautics and Space Administration (NASA). The paper provides a brief overview of System Health Management as an extension of control theory; describing how ATs and the calculation of FP and FN probabilities relate to this theory as an aspect of state estimation. This discussion leads to a detailed presentation of the methodology and an example showing how the calculations are performed, including the change in AT FP and FN rates resulting from the application of SDQ. To avoid proprietary and sensitive data issues, the example incorporates a mixture of open literature and fictitious reliability data, rather than the actual SLS data. Results presented in the paper demonstrate the effectiveness of the approach in providing quantitative estimates that bound the probability of a FP or FN abort determination.

Publication Year: 
2015
Publication Volume: 
6
Publication Control Number: 
070
Page Count: 
15
Submission Keywords: 
false positive detection
false negative detection
Submission Topic Areas: 
Health management system design and engineering
Standards and methodologies
Uncertainty Quantification and Management in PHM
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