Blade crack detection using variational model decomposition and time-delayed feedback nonlinear tri-stable stochastic resonance

Abstract

For centrifugal fans, the emergence of amplitude modulation (AM) components is a pivotal feature for blade crack fault. However, AM features extraction are challenging under strong interferences. A novel method is proposed to solve this problem using variational mode decomposition (VMD) and time-delayed feedback nonlinear tri-stable stochastic resonance (TFNTSR). Firstly, an improved degree of cyclostationarity (IDCS) index is constructed for parameters optimization. Then, intrinsic mode functions (IMFs) are obtained using the VMD method, and one of them which has the maximum IDCS value is selected. Finally, the selected IMF is further processed by the TFNTSR method, thereby completing the blade crack detection. Verified by simulations and experiments, VMD-TFNTSR method has a better performance on blade crack detection.