The invention discloses an analog circuit fault diagnosis method based on a support vector machine. The method comprises the following steps: according to typical fault conditions, circuit emulation is carried out to obtain an accessible point voltage value which is taken as the training sample of the support vector machine; the prior ant algorithm is improved and probability selection method andrandom selection method are used together to realize path selection; the RBF kernel function parameters (gamma, C) of the support vector machine is optimized by means of an improved ant algorithm; SVMis trained by the training sample with the trained result and error stored in a memory; the practical voltage signal of a to-be-tested circuit is measured and is input to the trained support vector machine; thus, the steady-state output of the support vector machine is the type of a fault, thereby completing pattern recognition and realizing fault diagnosis. The analog circuit fault diagnosis method has obvious advantages when used in small sample learning fault diagnosis; moreover, the method also has the advantages of fast speed, high accuracy and strong generalization capability.