Gaigai Cai

TL;DR: The authors introduce an iterative algorithm, called matching demodulation transform (MDT), to generate a time-frequency (TF) representation with satisfactory energy concentration, and the MDT-based synchrosqueezing algorithm is described to further enhance the concentration and reduce the diffusion of the curved IF profile in the TF representation of original syn chrosquEEzing transform.

TL;DR: In this paper, a sparsity-enabled signal decomposition method was proposed to extract fault features of gearboxes by analyzing the oscillatory behavior of the signal rather than the frequency or scale.

TL;DR: A nonconvex sparse regularization method for bearing fault diagnosis is proposed based on the generalized minimax-concave (GMC) penalty, which maintains the convexity of the sparsity-regularized least squares cost function, and thus the global minimum can be solved by convex optimization algorithms.

TL;DR: A method based on stacked CAE for automatic robust features extraction and fault diagnosis of rotating machinery is proposed and results show that the diagnosis accuracies of the proposed method are higher than those of the stacked autoencoder (AE) network under each SNR.

TL;DR: In this article, a reliability estimation approach to the cutting tools based on logistic regression model by using vibration signals has been proposed, which does not require any assumption about degradation paths and probability density functions of condition parameters.