1 August 1990 Investigation of neural networks for F-16 fault diagnosis: II. System performance
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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.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Richard J. McDuff, 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); doi: 10.1117/12.21155; https://doi.org/10.1117/12.21155

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