7.4
Case2MODscatterenergy.
...................120
7.5
Case
2
MOD
expected
value
and
scatter
energy
slopes.
. . . . 120
7.6
Case2RMSRrawanddecomposed................121
7.7
Case2RMSRscatterenergy.
..................121
7.8
Case
2
RMSR
expected
value
and
scatter
energy
slopes.
.
.
.
.
121
7.9
Case5MODrawanddecomposed.
...............123
7.10Case5MODscatterenergy.
...................123
7.11
Case
5
MOD
expected
value
and
scatter
energy
slopes.
. . . . 123
7.12
Case5RMSRrawanddecomposed..
.
.
.
.
.
.
.
.
.
.
.
.
.
.124
7.13Case5RMSRscatterenergy.
..................124
7.14
Case
5
RMSR
expected
value
and
scatter
energy
slopes.
.
.
.
.
124
A.1
Evolutionary
optimization
overview.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
136
A.2
Radialbasisnetwork........................137
List of Tables
3.1
Commonconditionindicators.
.................. 39
6.1
Normalstatemodelparameters
................. 86
6.2
Stepchangemodelparameters.
................. 87
6.3
Damagedstatemodelparameters................. 88
6.4
Testsetmodelparameters..................... 89
6.5
Progression
analysis
method
comparison
chart.
.
.
.
.
.
.
.
.
.
113
7.1
Authentictestcases.
.......................122
149
Bibliography
[1] CIVIL AVIATION AUTHORITY. Cap693, acceptable means of com-pliance, helicopter health monitoring, caa aad 001-05-99, 1999.
[2] Lionel Stuart Barry. Aircraft health and usage monitoring system. Patent EP0407179A1, 1991.
[3] Eric Bechhoefer and P.F. Bernhard Andreas. Hums optimal weighting of condition indicators to determine the health of a component. In American Helicopter Society 60th Annual Forum, Baltimore, USA, 2004.
[4] J.S. Bendat and A.G. Piersol. Random Data; Analysis and Measurement Procedures, Second ed. Wiley, New York, 1986.
[5] S. Charbonnier, C. Garcia-Beltan, C. Cadet, and S. Gentil. Trends extraction and analysis for complex system monitoring and decision support. Engineering Applications of Arti.cial Intelligence, 18:21–36, February 2005.
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