The on-site measured data of short-wave irregularities on urban rail transit track surfaces often exhibit non-stationary characteristics. A study was conducted on the non-stationary short-wave irregularity data of certain sections of Shanghai Metro Line 11 using a wavelet method based on multi-resolution and adaptability. The research demonstrates that wavelet basis functions can effectively identify local features of short-wave irregularity waveforms. Through the approximation and detail signals obtained from wavelet decomposition, significant irregularities at wavelengths of 20.298 m and 115.98 m were identified. Power spectrum analysis of these decomposed signals revealed the contributions of different waveforms to the power spectrum across various wavelength ranges. The wavelet spectra of underground lines, elevated straight sections, and curved sections with welded joints were calculated using the wavelet transform method and compared with the Sato spectrum and the short-wave spectrum from the China Academy of Railway Sciences. The results indicate that the wavelet analysis method can effectively process non-stationary data, providing a robust approach for comprehensively analyzing the characteristics of short-wave irregularities on urban rail transit track surfaces.