Shipboard machinery diagnostics and prognostics/condition based maintenance: A progress report

IEEE Aerospace Conference Proceedings

Volumn 6, Issue , 2000, Pages 277-292

  Hadden, George D ^a   Bergstrom, Peter ^a   Vachtsevanos, George ^b   Bennett, Bonnie Holte ^c   Van Dyke, Joe ^d  

^a HONEYWELL TECHNOLOGY CENTER   (United States)

^b GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^c Knowledge Partners of Minnesota   (United States)

^d Systems Analysis and Software Engineering   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER APPLICATIONS; EQUIPMENT TESTING; MAINTENANCE; MICROELECTROMECHANICAL DEVICES; MONITORING; SENSORS; SHIP EQUIPMENT; VIBRATIONS (MECHANICAL);

INTELLIGENT SIGNAL PROCESSING DEVICES; SHIPBOARD MACHINERY; SHIPBOARD MONITORING SYSTEMS; VIBRATION ANALYSIS;

SPACE APPLICATIONS;

EID: 0034432031     PISSN: 1095323X     EISSN: None     Source Type: Journal    
DOI: 10.1109/AERO.2000.877904     Document Type: Article

References (13)

1. Condition-based maintenance: Algorithms and applications for embedded high performance computing
2. Integrated diagnostics and prognostics systems
3. Elliptic and radial wavelet neural networks
4. An autonomous diagnostic/prognostic system for shipboard chilled water plants
5. Machinery diagnostics and prognostics/condition based maintenance: A progress report
6. Shipboard machinery diagnostics and prognostics/condition based maintenance: A progress report
7. Shipboard machinery condition based maintenance
8. Condition based maintenance for shipboard machinery
9. State-based feature recognition
10. An application of fuzzy logic and Dempster-Shafter theory to failure detection and identification
11. An intelligent approach to fault detection and identification
12. Real-time feature recognition in medical data
13. On the detection and identification of axial flow compressor instabilities