In order to improve the selectivity and quick action of generator loss of field (LOF) protection, a method for LOF protection based on support vector machine (SVM) for intelligent identification of trajectory is proposed. The measured impedance trajectory of the generator contains lots of generator operation information, and the motion characteristics can reflect the generator's operating state. First, the global and local features of the measured impedance trajectory of the generator are extracted, and the extracted motion feature sequence is calculated separately for statistical parameters to form 24-dimensional features. Then through principal component analysis of the feature space to reduce the dimensionality, the corresponding training input feature space is formed, and genetic simulated annealing algorithm is used for the SVM to optimize the parameters support. Finally, sample simulation verifies that this method can accurately identify the LOF. Compared with the traditional LOF protection, the proposed method improves the selectivity and quickness of the protection.