… this paper intends to review fault diagnosis methods based on convolutional networks more
… understand and promote the development of CNN technologies for machine fault diagnosis. …

… [26–28] and convolutional neural network [29–32]. In this paper, the utilization of convolutional
neural network (CNN) in diagnosing bearing fault diagnosis is reviewed. CNN is widely …

… Convolutional neural network (CNN) provides an efficient … Inspired by the idea of CNN, we
develop a novel diagnosis … CNN architecture is composed of dislocate layer, convolutional …

… achieve fast, reliable and high-quality diagnosis in an automatic manner. In this paper, a
novel fault diagnosis approach integrating Convolutional Neural Networks (CNN) and Extreme …

… These traditional shallow learning models can only provide limited diagnosis ability. In
summary, traditional intelligent fault diagnosis methods still have some obvious drawbacks as …

… in this paper is novel in the field of machinery fault diagnosis and is able to learn invariant
features based on the convolution and pooling architecture. Different from traditional CNN, a …

… for mechanical fault diagnosis. In this paper, a novel TCNN architecture is proposed in order
… 1, the 1-D raw vibration signals are first inputted into the first convolutional layer to achieve …

… Over the past few years, deep convolutional neural network (DCNN) has shown excellent …
In this paper, a fault diagnosis method based on a DCNN model consisting of convolutional …

… difficulties for fault diagnosis. Therefore, … convolutional neural network (CNN) for motor fault
diagnosis. Our contributions mainly fall into two aspects. First, we notice that each motor fault …

… In our opinion, the reason lies into the characteristic of the convolutional architecture of
CNN, which is able to overcome the small frequency shift of fault patterns by detecting the local …