The invention discloses a support vector machine and multi-body dynamics simulation-based high-voltage circuit breaker identification method. The method comprises the steps of building a three-dimensional model of a high-voltage circuit breaker, and calibrating and verifying the three-dimensional model; by changing size, material and property parameters of the three-dimensional model, performing analogue simulation on various faults of the high-voltage circuit breaker to obtain various corresponding mechanical property waveforms; performing waveform interception, mathematic morphological filtering and characteristic extraction processing on the mechanical property waveforms corresponding to the various faults to obtain an eigenvector sample set; based on a support vector machine and a one-to-many classification method thereof, training a classifier, and calculating the credibility of each classification; and inputting actually measured unknown fault eigenvectors to the training support vector machine, performing fault type identification to realize mechanical fault classification of the high-voltage circuit breaker, and finishing self-learning. According to the method, a large amount of physical simulation experiments do not need to be carried out; the faults of the high-voltage circuit breaker can be accurately identified; and the method has a self-learning function and a wide application prospect.