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

Li, Y; Pont, MJ; Jones, NB

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.

Citation

Li, Y., Pont, M., & Jones, N. (1999, April). A comparison of the performance of radial basis function and multi-layer perceptron networks in condition monitoring and fault diagnosis applications. Presented at International Conference on Condition Monitoring, Swansea, UK

• Presentation Conference Type: Other
• Conference Name: International Conference on Condition Monitoring
• Conference Location: Swansea, UK
• Start Date: Apr 12, 1999
• End Date: Apr 15, 1999
• Publication Date: Apr 1, 1999
• Deposit Date: Jul 27, 2015
• Keywords: Engine misfire detection, neural networks, multi-layer perception, radial basis function, condition monitoring. fault classification
• Additional Information: Event Type : Conference