Xiangsheng Gao

TL;DR: A CCPR method based on a one-dimensional convolutional neural network (1D-CNN) based on the influence of the network structural parameters and activation functions on the recognition performance is analyzed and discussed, and some suggestions for parameter selection are given.

TL;DR: In this article, the influence of configuration parameters on dynamic characteristics of machine tools in the working space has been suggested based on the orthogonal experiment method, where the configuration parameters are considered as four factors for dynamic characteristics.

TL;DR: An intelligent SPC method based on feature learning using multilayer bidirectional long short-term memory network (Bi-LSTM) to learn the best features from the raw data, which has obvious advantages over other methods in recognition accuracy, despite the HPR or CCPR.

TL;DR: The proposed fault diagnosis model of rolling bearing based on a multi-dimension input convolutional neural network (MDI-CNN) improves the recognition rate, robustness and convergence performance of the traditional convolution model and has good generalization ability.

TL;DR: Based on the excellent mechanical properties and remarkable surface lubrication mechanism of natural articular cartilages, one kind of cartilage-like composite material with a lubrication phase (Composite-LP) was developed by chemically grafting a thick hydrophilic polyelectrolyte brush layer onto the subsurface of a three-dimensional manufactured elastomer scaffold-hydrogel composite architecture as discussed by the authors .