A power supply ramping and current measurement based technique for analog fault diagnosis

Presents a methodology for fault diagnosis of analog circuits based on the observation of power supply currents. In the proposed technique, fault signature dictionaries are generated from the currents in the power supply bus. To obtain signatures rich in information for efficient diagnosis, the transistors in the circuit are forced to operate in all regions of operation by using a ramp signal at the supply instead of the conventional constant dc signal. The signatures are then clustered into different groups using a Kohonen neural network classifier. This technique has the potential to detect and diagnose single and multiple shorts as well as open circuits. The theoretical and experimental results of the proposed technique are verified using a CMOS Operational Transconductance Amplifier (OTA) circuit