Artificial circuit fault diagnosis system based on random forest

An artificial circuit fault diagnosis system based on a random forest of the present invention belongs to the fault diagnosis field, and comprises a fault simulation subsystem, a fault diagnosis subsystem and a man-machine interaction interface. The fault simulation subsystem is used to realize a simulation fault simulation circuit and a semi-physical fault simulation circuit, and output circuit data to the fault diagnosis subsystem. The fault diagnosis subsystem removes redundancy on the circuit data and then constructs an RF classifier and an RF rule base to diagnose faults. The semi-physical fault simulation circuit is characterized in that a programmable resistor card is added in a real circuit by a fault injection module to realize a resistor fault. When the RF classifier is used to diagnose faults, the reconstruction is carried out by the stored RF node data information, and the time of retraining the RF classifier is saved. According to the present invention, a plurality of fault mode simulation and fa