A Novel Prediction Method for Analog Circuits Based on Gaussian White Noise Estimation

Research on prediction about analog circuits is rarely conducted, and the only methods are prognosis of few special features extracted from output without guarantee of integrity and rationality of prognostic information, which hence influences prognostic precision. In this paper, a novel prediction method for analog circuits is proposed. In this method, time domain output waveforms in initial state and components degradation state are extracted at first, then white noise estimation is conducted to estimate the change between waveforms according to principles of noise estimation based on Kalman filter so as to obtain more reasonable fault indicators from more complete information, thereafter, a novel degradation tendency model of analog circuits is constructed according to newly obtained fault indicators, model adaption is conducted to the new model through particle filter, and prognostic method is conducted to remaining useful performance of analog circuits. Finally, experimental verification is conducted to the above conclusion.