Investigation of neural networks for F-16 fault diagnosis: II. System performance

Richard J. McDuff; Patrick K. Simpson

doi:10.1117/12.21155

1 August 1990 Investigation of neural networks for F-16 fault diagnosis: II. System performance

Richard J. McDuff, Patrick K. Simpson

Proceedings Volume 1294, Applications of Artificial Neural Networks; (1990) https://doi.org/10.1117/12.21155
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

Abstract

We have examined the use of neural networks as a potential method of solving the multiple fault diagnostics problem that is when one symptom leads to several faults many symptoms leadto one fault or many symptoms lead to many faults. Current methods addressing this problem are brittle and slow. We have approached diagnostics from a pattern classification perspective in that we have constructed an input pattern from symptoms and classified that symptom pattern to an appropriate output class that corresponds to the fault that occurred. The system description was described in the first part of this two-part paper . In this second part we will report on the performance of the system. 1.

Citation Download Citation

Richard J. McDuff and Patrick K. Simpson "Investigation of neural networks for F-16 fault diagnosis: II. System performance", Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); https://doi.org/10.1117/12.21155

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