Ulster University Logo

Ulster Institutional Repository

A comparison of the performance of radial basis function and multi-layer perceptron networks in condition monitoring and fault diagnosis applications

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Li, Yuhua, Pont, MJ and Jones, NB (1999) A comparison of the performance of radial basis function and multi-layer perceptron networks in condition monitoring and fault diagnosis applications. In: CONDITION MONITORING `99, PROCEEDINGS, SWANSA, WALES. UNSPECIFIED. 6 pp. [Conference contribution]

Full text not available from this repository.

Abstract

In this paper, we provide a detailed comparison of multi-layer Perceptron (MLP) and radial basis function (RBF) networks in embedded, microcontroller-based condition monitoring and fault diagnosis applications. On the basis of the studies presented here, it is concluded that the MLP provides similar levels of performance to the RBF network while exerting a low computational load on the processor.

Item Type:Conference contribution (Paper)
Keywords:engine misfire detection; neural networks; multi-layer perception; radial basis function; condition monitoring; fault classification
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:5978
Deposited By:Dr Yuhua Li
Deposited On:09 Mar 2010 16:14
Last Modified:09 Mar 2010 16:14

Repository Staff Only: item control page