… fault diagnosis approach is proposed for RM based on a novel continuous wavelet transform-local
binary convolution neural network (… -LBCNN model, and the fault condition of RM can …

… issue and elevate the diagnostic accuracy of the conventional methods, a novel fault
diagnosis method based on local binary temporal convolutional neural network (LBTCNN) is …

… on binary matrix encoding and convolutional neural network is proposed in this paper. Its
main purpose is to carry out a real-time multi-classification and multi-level fault diagnosis using …

… In this study, we propose a binary neural network accelerator and implement it in a field…
(FPGA) for bearing fault diagnosis. By using a one-dimensional convolutional neural network, we …

… fault diagnosis purpose at the edge. First, the floating-point DNN is converted to a binary neural
network (… Among them, one of the typical DL models, namely convolution neural network (…

… To compensate for the possible accuracy decrease resulting from binarization, we utilize
RF as a classifier to process binary features and ReliefF as the attribute evaluation measure to …

… features for fault diagnosis. In this article, a novel three-step intelligent fault diagnosis method
is … In the fault dataset construction step, multiple binary training datasets are constructed to …

… problem is transformed into a binary classification problem … fault diagnosis model based on
CNN-GRU neural networks is proposed. It is an end-to-end fault diagnosis model to diagnose …

… 1 is considered for binary classification fault diagnosis problem in this study. A body-fixed
coordinate system is defined with its origin at the UAV’s center of mass and its axes (xb, yb, …

… Design and application of unsupervised convolutional neural networks integrated with
deep belief networks for mechanical fault diagnosis. In 2017 Prognostics and system health …