Intelligent fault diagnosis method based on full 1-D convolutional generative adversarial network
Q Guo, Y Li, Y Song, D Wang… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Data-driven fault diagnosis is essential for the reliability and safety of industry equipment.
However, the lack of real labeled fault data make the machine learning-based diagnosis …
However, the lack of real labeled fault data make the machine learning-based diagnosis …
Federated zero-shot industrial fault diagnosis with cloud-shared semantic knowledge base
B Li, C Zhao - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
Recently, a considerable literature has grown up around the few-sample fault diagnosis
task, in which few samples of fault data are available for model training. The lack of fault …
task, in which few samples of fault data are available for model training. The lack of fault …
Fault description based attribute transfer for zero-sample industrial fault diagnosis
L Feng, C Zhao - IEEE Transactions on Industrial Informatics, 2020 - ieeexplore.ieee.org
In this article, a challenging fault diagnosis task is studied, in which no samples of the target
faults are available for the model training. This scenario has hardly been studied in industrial …
faults are available for the model training. This scenario has hardly been studied in industrial …
A label description space embedded model for zero-shot intelligent diagnosis of mechanical compound faults
It has always been an issue of significance to diagnose compound faults of machines.
Existing intelligent diagnosis methods have to be trained by sufficient data of each …
Existing intelligent diagnosis methods have to be trained by sufficient data of each …
Open-set fault diagnosis via supervised contrastive learning with negative out-of-distribution data augmentation
Fault diagnosis in an open world refers to the diagnosis tasks that need to cope with
previously unknown faults in the online stage. It faces a great challenge yet to be addressed …
previously unknown faults in the online stage. It faces a great challenge yet to be addressed …
A novel metric-based model with the ability of zero-shot learning for intelligent fault diagnosis
Intelligent fault diagnosis plays an important role in maintaining the safe and reliable
operation of rotating machinery. However, the data collected in real engineering scenarios …
operation of rotating machinery. However, the data collected in real engineering scenarios …
An effective zero-shot learning approach for intelligent fault detection using 1D CNN
Data-driven fault detection techniques have attracted extensive attention in engineering,
industry and many other areas in recent years. In many real applications, the following …
industry and many other areas in recent years. In many real applications, the following …
Auxiliary information-guided industrial data augmentation for any-shot fault learning and diagnosis
The label scarcity problem widely exists in industrial processes. In particular, samples of
some fault types are extremely rare; even worse, the samples of certain faults cannot be …
some fault types are extremely rare; even worse, the samples of certain faults cannot be …
Intelligent fault diagnosis of machines with small & imbalanced data: A state-of-the-art review and possible extensions
The research on intelligent fault diagnosis has yielded remarkable achievements based on
artificial intelligence-related technologies. In engineering scenarios, machines usually work …
artificial intelligence-related technologies. In engineering scenarios, machines usually work …
Variational autoencoder based on distributional semantic embedding and cross-modal reconstruction for generalized zero-shot fault diagnosis of industrial processes
M Mou, X Zhao, K Liu, Y Hui - Process Safety and Environmental Protection, 2023 - Elsevier
The traditional fault diagnosis models cannot achieve good fault diagnosis accuracy when a
new unseen fault class appears in the test set, but there is no training sample of this fault in …
new unseen fault class appears in the test set, but there is no training sample of this fault in …