Fault diagnosis of analog circuit based on support vector machines

An innovative method based on support vector machines is presented to diagnose the fault of analog circuit. Firstly, in order to get enough fault samples, the circuit program is compiled in MATLAB software to obtain expressions of output signals. Secondly, fault samples are sent into Support Vector Machines to train Support Vector Machines. Thirdly, the test samples are classified by trained Support Vector Machines. Finally, an example of analog circuit fault diagnosis is provided. The result shows that this method has the advantages of simple algorithm, high efficiency, high accuracy, great capability in generalization and classification.