Reassignment-enable reweighted sparse time-frequency analysis for sparsity-assisted aeroengine rub-impact fault diagnosis. (15th January 2023) - Wang, Shibin; Cheng, Chuanyi; Zhou, Jianghan; Qin, Fuhua; Feng, Yining; Ding, Baoqing; Zhao, Zhibin; Chen, Xuefeng
Highlights: A reassignment-enable reweighted sparse time–frequency method is proposed for the feature extraction of signals with fast-varying IF. An acceleration strategy is proposed for FISTA to speed up the convergence for solving the Re 2 STF model. The simulation study proves that Re 2 STF has the best TF performance among the considered methods. The application in aeroengine vibration analysis verifies that Re 2 STF is effective for aeroengine rub-impact fault diagnosis. Abstract: Time-frequency analysis (TFA) is an effective tool for the feature extraction of nonstationary signals. However, the energy concentration of the TF representation (TFR) obtained by conventional TFA is weakened when the instantaneous frequency (IF) of signals varies fast, which adversely affects the feature extraction and reconstruction. In this paper, a reassignment-enable reweighted sparse TF method (Re 2 STF) is proposed to achieve high energy concentration as well as highly accurate reconstruction when analyzing signals with fast-varying IF, and thus is effective to the vibration analysis of aeroengine rub-impact fault. A reweighted sparse TF model is constructed, which iteratively employs the TF reassignment representation into the reweighted strategy to suppress noise and match the fast-varying TF structure better. In particular, the reassignment-enable weight can highlight the TF ridge and suppress the TF coefficients elsewhere. Furthermore, an effective acceleration strategy for the fast iterative shrinkage threshold algorithm is proposed to speed up the model solving. The simulation study and the application in the vibration analysis of a dual-rotor turbofan engine show the improvement of Re 2 STF in denoising, TF energy concentration and reconstruction, thus proving the effectiveness in aeroengine rub-impact fault diagnosis.