With the application of new energy in grid-connected system and the development of ultra-high voltage direct current transmission,the grid's requirements for reactive power regulation have gradually increased. Considering that,large-scale synchronous condensers have been put into use again. However,it is difficult to extract the characteristic signal of the inter-turn short-circuit fault in rotor windings of synchronous motors. In order to improve the stability of condensers,a certain relationship between the field current and the number of turns is derived using the Parker equation in the dq coordinate system,and the differential equation simulates the excitation current. Then the characteristic energy value of the fault signal is extracted through wavelet packet decomposition and reconstruction,and it is input to the radial basis function neural network for fault diagnosis. It is proved by Matlab simulation that the diagnostic method proposed in this paper can effectively detect the degree of short-circuit faults among the turns of the rotor in condensers.