Heavy rainfall has posed a great challenge to the service performance of high-speed rail (HSR) substructure, resulting in a reduction in the ride quality and safety of high-speed trains. To carry out proper repair work for the substructure, it is imperative to realize efficient identification of precipitation-induced subgrade defects. To this end, this paper aims to extract the features of typical precipitation-induced subgrade defects from the multiple track inspection data to provide a basis for defect identification. Firstly, the geotechnical site investigation including Ground Penetrating Radar (GPR) detection, moisture content test, and dynamic cone penetration (DCP) test of a typical defective spot is performed to determine the condition of the subgrade after heavy rainfall; then, the analysis methods of track inspection data are introduced; finally, the track geometry data and carbody acceleration data of four typical defective sections are analyzed, and the time-domain, frequency-domain and discrete wavelet transform (DWT)-based features which are highly correlated with the precipitation-induced subgrade defects are extracted. The results show that the feature indexes extracted from track surface irregularity and carbody vertical acceleration increase significantly after heavy rainfall; the long wavelength components (8 m and above) of both track irregularity and carbody vibration are more sensitive to the subgrade defects, which is reflected by the sharp increase of the DWT-based features at some levels corresponding to long wavelength ranges. The results of defect feature extraction based on the track inspection data agree well with the geotechnical site investigation results, which demonstrate the feasibility of utilizing multiple track inspection data to identify the typical precipitation-induced subgrade defects.