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2007

Evolving an artificial neural network classifier for condition monitoring of rotating mechanical systems

9 years 4 months ago
Evolving an artificial neural network classifier for condition monitoring of rotating mechanical systems
We present the results of our investigation into the use of Genetic Algorithms (GAs) for identifying near optimal design parameters of diagnostic systems that are based on Artificial Neural Networks (ANNs) for condition monitoring of mechanical systems. ANNs have been widely used for health diagnosis of mechanical bearing using features extracted from vibration and acoustic emission signals. However, different sensors and the corresponding features exhibit varied response to different faults. Moreover, a number of different features can be used as inputs to a classifier ANN. Identification of the most useful features is important for an efficient classification as opposed to using all features from all channels, leading to very high computational cost and is, consequently, not desirable. Furthermore, determining the ANN structure is a fundamental design issue and can be critical for the classification performance. We show that a GA can be used to select a smaller subset of features tha...
Abhinav Saxena, Ashraf Saad
Added 08 Dec 2010
Updated 08 Dec 2010
Type Journal
Year 2007
Where ASC
Authors Abhinav Saxena, Ashraf Saad
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