Abstract: With the development of VLSI,conventional contact test is constrained in some occasions.Aiming at insufficient information of analog circuit electronic test,electronic and non-electronic information is combined as fault feature signature in the paper.Self-Organizing Feature Map (SOFM) Neural network is applied to analog circuit fault diagnosis.Voltage and temperature information is extracted as fault feature information,then processed,which is sent into neural network as input sample to detect circuit fault.Using the competition of output level neurons of SOFM,the winning neuron is attained and the fault recognition for sample data is classified.Simulation results show that fusion diagnosis has more satisfactory accuracy compared with single information diagnosis.