Neural Network Application to Aircraft Electrical System

Principal Investigator: Mohamed A. El-Sharkawi

Sponsor: Boeing Company

Abstract: Although the discipline has been around for quite some time, interest in the application of artificial neural networks has exploded in the last decade. Within three years, five new journals dedicated only to artificial neural networks appeared. A number of international conferences have attracted thousands of participants. Japan, Europe and the United States have each launched multi-million dollar research programs into the field of artificial neural networks and their applications. The reason for the excitement is the incredible potential computational abilities of the neural net and the ability of modern technology to implement the required neural net architectures. Neural networks have found use in numerous fields, including speech recognition, stock market forecasting, mortgage brokering, and remote sensing. Since the neural net is amenable to learning inherently nonlinear and/or complex relationships from examples, a number of system problems are potentially applicable to neural net solutions. Neural networks are especially suited for several electrical system problems such as stability assessment, harmonic evaluation and detection, fault diagnosis, adaptive control, and alarm processing. The purpose of this research is to evaluate the Artificial Neural Network technology for aviation electrical systems. This includes, electric drives control, fault detection of electrical equipment, and stability assessment.

For more info, please contact M. A. El-Sharkawi