… adaptive decoupling strategy is proposed in this paper. The adaptive decoupling strategy …
The second is to decouple the category control signal from the generator network structure. …

… is too high to allow perfect decoupling, two approximate decoupling methods are
introduced. One utilizes rank reduction of the modelerror/fault entry matrix via singular value …

… requires massive labeled data for compound fault diagnosis, which is difficult and time-… This
paper presents a novel decoupling attentional residual network for compound fault diagnosis…

… the interpretation of mode-decoupling of MDAE are performed … explanation on mode-decoupling
of MDAE illustrate that the … and interpretation on mode-decoupling of our MDAE. Finally, …

… For rapid and accurate AD, a stable knowledge distillation decoupling net … Then, a causal
decoupling framework is suggested to … Gui, “Metric learning-based fault diagnosis and anomaly …

… the statics before dynamics modeling, which may reduce the accuracy of fault diagnosis. …
fault isolation strategies, we provide the DMD-based monitoring and fault isolation strategies …

… neural network (GNN) augmented with decoupling adversarial learning is proposed. First, …
, a multi-domain decoupling adversarial learning strategy is proposed to achieve the fine-…

… interpretably transferring fault-related components. First, this paper constructs a neural
basis function decoupling module to disentangle the signal into fault-related and fault-unrelated …

… We propose a transferable decoupling multi-scale autoencoder (TDMSAE) for mechanical
fault diagnosis to address this problem. TDMSAE includes three modules: the feature …

… Over past decades, it has been widely recognized that vibration analysis can be used
effectively for mechanical fault diagnosis. In the early 1940s, pioneering investigation on …