Analog Circuit Fault Detection by Impulse Response-Based Signature Analysis

This paper presents a method for the detection of parametric faults in linear filters with the help of impulse response which is studied on the basis of cross-correlation, a statistical metric. Impulse input is generated with delay flip flops and R–C circuit with minimum circuit complexity. Cross-correlation of impulse responses of the faulty and non-faulty circuits is fitted with Gaussian function. Component tolerances are mapped to statistical metric spaces in terms of Gaussian fitting parameters by Monte Carlo simulation. The proposed method is validated with simulated (using UMC-180 nm technology in CADENCE Virtuoso platform) as well as experimental results. Two benchmark analog filter circuits, second-order Sallen–Key band-pass filter and fourth-order Chebyshev low-pass filter, are considered as test circuits. The present method requires minimum circuit complexity and computational effort. The proposed fault detection technique is applicable for any linear analog circuit.