A automatic fault diagnosis technique based on fuzzy classification is proposed for analog circuits analysis. The classifier performance is very similar to that of a radial basis function neural classifier. Taking into account noise and non-faulty parameter tolerance effects, the diagnosis system is able to locate faults both at component and subsystem levels with low error.
Catelani, M., Fort, A., Bigi, M., Singuaroli, R. (2000). Soft fault diagnosis in analogue circuits: A comparison of fuzzy approach with radial basis function networks. In Proceedings of the 17th IEEE Instrumentation and Measurement Technology Conference [Cat. No. 00CH37066] (pp.1493-1498). New York : IEEE [10.1109/IMTC.2000.848722].
Soft fault diagnosis in analogue circuits: A comparison of fuzzy approach with radial basis function networks
Fort Ada;
2000-01-01
Abstract
A automatic fault diagnosis technique based on fuzzy classification is proposed for analog circuits analysis. The classifier performance is very similar to that of a radial basis function neural classifier. Taking into account noise and non-faulty parameter tolerance effects, the diagnosis system is able to locate faults both at component and subsystem levels with low error.
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https://hdl.handle.net/11365/1321202