Analog Circuits Soft Fault Diagnosis Using Rényi’s Entropy

An analog circuit soft fault diagnosis method using Rényi’s entropy is proposed. This method focuses on extracting the entropy information contained in the probability density function (PDF) of the output of the circuit under test (CUT), which is sensitive to the parameters of circuits. Firstly, using the Lagrange multiplier method with Rényi’s entropy deduces PDF. Then the parameter α of Rényi’s entropy is estimated adaptively by employing the output of CUT through the maximum likelihood estimation method. Finally, the value of Rényi’s entropy can be calculated using the PDF and α parameter. The divergence between the Rényi’s entropy corresponding to the fault and fault free circuits is adopted to detect the fault. The method can detect soft fautls, including the single fault and multiple faults, without complicated models and mass of data, and also without interrupting the inherent connections. We conduct experiments respectively on two circuits that are implemented on an actual circuit board. The effectiveness of the proposed method is demonstrated by the result of the experiment.