Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.1/2341
Título: Identification-based condition monitoring using neural network approach
Autor: Pashkevich, A.
Ruano, A. E.
Kulikov, G. G.
Kazheunikau, M.
Palavras-chave: Neural networks
Condition monitoring
Identification
Control charts
Data: 2003
Citação: Pashkevich, A.; Ruano, A. E.; Kulikov, G.; Kazheunikau, M. Identification-based condition monitoring using neural network approach, Trabalho apresentado em IFAC Int Conference on Intelligent Control Systems and Signal Processing (ICONS 2003), In IFAC Int Conference on Intelligent Control Systems and Signal Processing (ICONS 2003), Faro, 2003.
Resumo: The paper focuses on enhancement of condition monitoring techniques in application to hydro- and electromechanical servomechanisms, which are widely used both in industrial robots and aircraft equipment. Its particular contribution lies in the area of neural network application for identification data analysis, which allows early diagnosis of process faults, while the plant is still operating in a controllable region. The proposed technique has been implemented in a software tool that allows to automate the decision-making process and to visualize the analysis results.
Peer review: yes
URI: http://hdl.handle.net/10400.1/2341
Aparece nas colecções:FCT2-Artigos (em revistas ou actas indexadas)

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