TY - JOUR N2 - Considering the problem to diagnose incipient faults in nonlinear analog circuits, a novel approach based on fractional correlation is proposed and the application of the subband Volterra series is used in this paper. Firstly, the subband Volterra series is calculated from the input and output sequences of the circuit under test (CUT). Then the fractional correlation functions between the fault-free case and the incipient faulty cases of the CUT are derived. Using the feature vectors extracted from the fractional correlation functions, the hidden Markov model (HMM) is trained. Finally, the well-trained HMM is used to accomplish the incipient fault diagnosis. The simulations illustrate the proposed method and show its effectiveness in the incipient fault recognition capability. L1 - http://journals.pan.pl/Content/89894/PDF/Journal10178-VolumeXIX%20Issue2_03paper.pdf L2 - http://journals.pan.pl/Content/89894 PY - 2012 IS - No 2 EP - 218 DO - 10.2478/v10178-012-0018-7 KW - nonlinear circuits KW - fault diagnosis KW - Volterra series KW - fractional correlation KW - hidden Markov model (HMM) A1 - Yong Deng A1 - Yibing Shi A1 - Wei Zhang PB - Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation DA - 2012 T1 - Diagnosis of Incipient Faults in Nonlinear Analog Circuits SP - 203 UR - http://journals.pan.pl/dlibra/publication/edition/89894 T2 - Metrology and Measurement Systems ER -