DocumentCode :
1737422
Title :
A new method of plotting and navigating self organising maps for improved condition monitoring and prognosis
Author :
Burton, Bruce ; Harley, Ronald G.
Author_Institution :
Sch. of Electr. & Electron. Eng., Natal Univ., Durban, South Africa
Volume :
2
fYear :
2000
fDate :
2000
Firstpage :
980
Abstract :
This paper proposes a powerful new method for plotting self organising maps which enables more effective convergence analysis for training algorithms, and facilitates clear identification and distinction of major and minor class or feature boundaries. A simple example is presented to show how these boundaries enable direct interactive and automatic classification, without an output classification layer, and facilitate adaptive trajectory analysis for temporal condition monitoring with inherent time to failure prediction capabilities
Keywords :
classification; condition monitoring; failure analysis; identification; learning (artificial intelligence); reliability theory; self-organising feature maps; adaptive trajectory analysis; class boundaries; condition monitoring; condition prognosis; convergence analysis; distinction; feature boundaries; identification; navigating; plotting; self organising maps; temporal condition monitoring; time to failure prediction; training algorithms; Algorithm design and analysis; Clustering algorithms; Condition monitoring; Failure analysis; Navigation; Neural networks; Neurons; Power engineering and energy; Training data; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industry Applications Conference, 2000. Conference Record of the 2000 IEEE
Conference_Location :
Rome
ISSN :
0197-2618
Print_ISBN :
0-7803-6401-5
Type :
conf
DOI :
10.1109/IAS.2000.881951
Filename :
881951
Link To Document :
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