The successful application of time–frequency (TF) analysis has demonstrated its effectiveness in analyzing time-varying signals in industrial engineering. As a novel high-resolution TF analysis (TFA) method, the reassignment method (RM) and related techniques have gained considerable attention from academics recently. Despite certain merits of these techniques, their limitations prevent them from being utilized for practical data analysis. In this article, a novel TFA methodology is presented for investigating the nonstationary properties of signals with strong time variance. Specifically, the proposed approach enhances synchrosqueezing transform (SST) along the frequency direction and adopts the reassigning extraction operator (REO) to obtain a highly concentrated TF representation (TFR) and more accurate instantaneous frequency (IF) estimation, while possessing perfect signal reconstruction capability. Moreover, the integration of REO with the ridge detection technique enables the adaptive decomposition of multicomponent signals. Through comparison with some advanced methods in simulated signals and fault signals, the efficacy and advantages of this approach are demonstrated.