Development of False Alarm Mitigation Techniques Navy SBIR FY2005.1 Sol No.: Navy SBIR FY2005.1 Topic No.: N05-028 Topic Title: Development of False Alarm Mitigation Techniques Proposal No.: N051-028-0497 Firm: Intelligent Automation Corporation 13029 Danielson Street Suite 200 Poway, California 92064 Contact: Joel Bock Phone: (858) 679-4140 Web Site: www.iac-online.com Abstract: An essential premise motivating the Joint Strike Fighter Prognostics and Health Management (JSF-PHM) approach is the capability of correctly detecting faults in components or subsystems. Whether a fault is declared according to time series recordings by monitored on-board sensors, or by sophisticated reasoning algorithms that recognize slow changes in behavior as a component degrades over time, fault detection must be performed correctly. Otherwise, failed components may not be replaced as necessary, or one may be unnecessarily serviced due to a false alarm. Both types error interfere with the attainment of AL objectives of minimizing aircraft support and logistics costs. JSF-PHM demands novel algorithmic methods to eliminate false alarms. This is a challenging task, since classification algorithms intended to detect anomalies (unrecognized faults) learn data probability distributions in known fault condition space. Extrapolation outside the training data is problematic; however this is exactly the region where anomalies are expected to occur. Faced with an anomalous condition, proper discrimination between "fault" and "no-fault" will determine the overall false alarm rate of the PHM system. This proposal describes a novel means to achieve a minimal false alarm rate at a given, fixed level of statistical confidence. Benefits: Condition-based monitoring cannot effectively diagnose faults or predict remaining lifetime of components if false alarms are present at the output of reasoning algorithms. Minimizing false alarms and the associated problem of anomaly detection in real-time sensor data are unsolved problems in a practical sense. Therefore, the methodology that is proposed here has significant application to other systems where accurate monitoring of multiple sensors is a requirement. IAC has developed a good working relationship with key individual in Pratt & Whitney's Commercial Aircraft Engines Division. Pratt & Whitney has expressed interest in transitioning the Phase II technology into their ongoing commercial engine monitoring program. The fault minimization system may have considerable potential commercial application in products where faults are to be reliably detected on an automatic basis. Examples include diagnosis of impending disk failures in personal computers, fault detection processing in automobiles, and other consumer electronics that may benefit from reliable diagnostics and diagnostics. Return