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3. Phase-space dissimilarity measures for the airgap-offset seeded-fault. Columns correspond to individual three-phase voltages, with the same parameters as Fig. 2. Dataset No. 1 is for the nominal (no fault) state. (s) 2−3 are for two different airgap-offset faults. 29 Fig. 4. Phase-space dissimilarity measures for the airgap-offset seeded-fault. Colums correspond to individual three-phase currents, with the same parameters as Fig. 2. Dataset No. 1 is for the nominal (no fault) state. (s) 2−3 are for two different airgap-offset faults.

24 Table 8. 2: Collaborators map potential commercialization 09/03 09/03 09/03 09/03 Milestone/task description REFERENCES 1. M. W. Golay and C. W. Kang, “On-Line Monitoring for Improved Nuclear Power Plant Availability and Operational Advice -Active Equipment Monitoring: Rotating Machinery,” pp. 12−13, MIT-ANP-TR-057, Vol. I, Massachusetts Institute of Technology, February 1998. 2. James E. Campbell and Bruce M. 1),” Nuclear Energy Research Initiative (NERI), “Smart” Equipment and Systems to Improve Reliability and Safety in Future Nuclear Power Plant Operations, September 2001.

F). This report also presents results of extensive tests, showing that the same methodology provides robust and timely failure forewarning for a variety of equipment. One previous NERI5 project showed failure forewarning for a single pump-lube system. Another previous NERI project6 provided different scaling relationships for 23 each machine failure. In contrast to these very limited demonstrations, this project provides a single, general, robust approach for failure prognostication for several machines and different kinds of failure.

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