Wind turbine vibration monitoring under variable speed operation requires separating nonstationary rotor-order components whose frequencies and operating intervals depend on operating state. These components can occupy local support regions in the short-time Fourier transform (STFT) plane rather than fixed spectral bands or continuous ridges. This study presents time-frequency mode decomposition (TFMD), a segmentation-based method that estimates connected STFT support regions and reconstructs one mode from each region. TFMD selects STFT coefficients with high magnitude, groups them by connected component labeling, filters small regions, expands retained support regions with mask dilation and conflict resolution, and reconstructs modes by inverse STFT. In a synthetic response with six operating states, TFMD separates the components of each state and produces low reconstruction error without specifying the number of components in advance. In a controlled wind turbine blade strain experiment, the first decomposition reconstructs nine modes whose peak frequencies lie near the nominal once per revolution frequencies and whose energies are concentrated in the corresponding operating intervals. Residual decomposition further reveals weaker harmonic structure. These results support TFMD as a practical candidate for vibration analysis under variable speed operation, while offshore field use requires validation under environmental loading and with measured operating references.