In this paper, a global average pooling convolutional neural network based on CNN is
proposed for mechanical fault sound detection, which called as GCMD. To solve the data …

Imbalance is a typical characteristic of data in the field of intelligent fault diagnosis. As a data
augmentation method that both balances data and extends information, the generative …

Generative models have been applied in many fields and can be evaluated with many
methods. In the evaluation of generative models, the proper evaluation metric varies with the …

In the last decade, predictive maintenance has attracted a lot of attention in industrial
factories because of its wide use of the Internet of Things and artificial intelligence …

System health management is of upmost importance with today's sensor integrated systems
where a constant stream of data is available to feed information about a system's health …

Purpose The mechanical fault diagnosis method based on deep learning mainly uses single-
scale convolution kernels to extract fault features, which is difficult to extract fault feature …

With the rapid development of modern industry and artificial intelligence technology, fault
diagnosis technology has become more automated and intelligent. The deep learning …

Imperfect data, such as data scarcity and imbalance, have a negative impact on intelligent
fault diagnosis. Generative adversarial networks (GANs) have proven to be a potential …

With the rapid development of machine learning and deep learning, neural-network-based
pattern recognition techniques have become a trend for distributed acoustic sensing (DAS) …

In order to implement rail crack detection with acoustic emission (AE) technology in the
actual application, an important problem to be solved is how to overcome the noise …