Local time-reassigned synchrosqueezing transform and its application in bearing fault characteristic extraction.

• A new time-reassignment strategy inspired by ideal time–frequency analysis is proposed. • An efficient impulse feature extraction algorithm is derived from the sharpened time–frequency representation. • Algorithm performance is verified on complex bearing fault signals, such as variable speed conditions and multi-point defects. Rolling bearing fault signals and other types of impulse signals present transient broadband and fast time-varying characteristics in the time–frequency plane, which makes accurately locating the time–frequency trajectory of the signal a challenging task. In this paper, a new time–frequency analysis method is proposed to achieve a high energy-concentrated time–frequency representation for impulsive-like signals. At first, the points on the time–frequency ridges are detected to construct a fixed point set as the reassignment target of the fuzzy energy. Then the local blurred energy is directly assigned to the nearest ridge according to the reassignment direction of time–frequency points. The proposed method ensures a high concentration of energy and supports perfect signal reconstruction. The results of numerical validation prove that the new time–frequency analysis method has excellent noise robustness and energy concentration capability. Finally, the application of bearing fault diagnosis under multiple operating conditions confirms the excellence in the fault diagnosis field. [ABSTRACT FROM AUTHOR]