论文信息 - A fuzzy approach for soft fault detection in analog circuits

A fuzzy approach for soft fault detection in analog circuits

Abstract An automatic fault diagnosis technique based on a fuzzy approach is presented and its performance is analyzed by means of two examples. The proposed technique is applied to the detection and the isolation of single soft faults in analog electronic circuits. Both faults at component and sub-system level are considered. A ‘simulation before test’ approach is followed: a fault dictionary is a priori generated by collecting signatures of different fault conditions simulated in the frequency domain. A fuzzy classifier is trained by data contained in the fault dictionary and used to process the circuit under test response during test phase. The effects of noise and of non-faulty parameter tolerance are taken into account.

[1] Mathukumalli Vidyasagar,et al. A Theory of Learning and Generalization: With Applications to Neural Networks and Control Systems , 1997 .

[2] Marcantonio Catelani,et al. Fault diagnosis of electronic analog circuits using a radial basis function network classifier , 2000 .

[3] Bernd Fritzke,et al. Growing cell structures--A self-organizing network for unsupervised and supervised learning , 1994, Neural Networks.

[4] Marcantonio Catelani,et al. A measurement system for fault detection and fault isolation of analog circuits , 1999 .

[5] Mathukumalli Vidyasagar,et al. Statistical learning theory and randomized algorithms for control , 1998 .

[6] Marcantonio Catelani,et al. On the application of neural networks to fault diagnosis of electronic analog circuits , 1996 .

[7] Bernd Fritzke,et al. The LBG-U Method for Vector Quantization – an Improvement over LBG Inspired from Neural Networks , 1997, Neural Processing Letters.

[8] H. Chernoff. A Measure of Asymptotic Efficiency for Tests of a Hypothesis Based on the sum of Observations , 1952 .

[9] Roberto Tempo,et al. Probabilistic Robustness Analysis and Design of Uncertain Systems , 1999 .