Xiaofeng Han

TL;DR: The article preprocesses the composite fault with ensemble empirical mode decomposition (EEMD) and then reconstructs the intrinsic mode function with the same time scale and proposes kurtosis spectral entropy as the objective function and uses the proposed method to search the complex fault pulse signals in strong noise environment.

TL;DR: A multi-objective particle swarm optimization (MOPSO) algorithm is proposed to optimize the parameters of VMD, and it is applied to the composite fault diagnosis of the gearbox.

TL;DR: The results of the simulation signal analysis show that the proposed MKSED method is superior to MED, and the proposed method is applied to bearing fault diagnosis, which verifies its ability to extract continuous impact.

TL;DR: The newly proposed neural network named capsules network takes into account the size and location of the image and is applied in intelligent fault diagnosis, so as to improve the classification accuracy of Intelligent fault diagnosis.

TL;DR: A method to optimize VMD by using the immune fruit fly optimization algorithm (IFOA) is proposed and the method is applied to the fault extraction of a simulated signal and a measured signal of a wind turbine gearbox, and the fault frequency is successfully extracted.