Research graph
References from MSA-Mamba: A Frequency-Enhanced Multi-Scale Adaptive State Space Model for Motor Fault Diagnosis. Local targets link to admitted publications; unresolved targets remain external evidence.
A review on vibration monitoring techniques for predictive maintenance of rotating machinery
10.3390/eng4030102 · 2023 · External reference
10.3390/app15031389
10.3390/app15031389 · External reference
Intelligent fault diagnosis technology for mechanical equipment: Current status and development
10.63313/sd.2002 · 2025 · External reference
Industrial intelligence-driven production and operations management
10.1080/00207543.2023.2207956 · 2023 · External reference
Industrial intelligence and industrial structure change: Effect and mechanism
10.1016/j.iref.2024.04.002 · 2024 · External reference
A review of data-driven machinery fault diagnosis using machine learning algorithms
10.1007/s42417-022-00498-9 · 2022 · External reference
Extraction of local and global features by a convolutional neural network–long short-term memory network for diagnosing bearing faults
10.1177/09544062211016505 · 2022 · External reference
A novel local binary temporal convolutional neural network for bearing fault diagnosis
10.1109/tim.2023.3298653 · 2023 · External reference
Global contextual residual convolutional neural networks for motor fault diagnosis under variable-speed conditions
10.1016/j.ress.2022.108618 · 2022 · External reference
A convolutional neural network method based on Adam optimizer with power-exponential learning rate for bearing fault diagnosis
10.21595/jve.2022.22271 · 2022 · External reference
Multiscale residual attention convolutional neural network for bearing fault diagnosis
10.1109/tim.2022.3196742 · 2022 · External reference
10.3390/machines11070746
10.3390/machines11070746 · External reference
Long-term sequence dependency capture for spatiotemporal graph modeling
10.1016/j.knosys.2023.110818 · 2023 · External reference
Dynamic temporal dependency model for multiple steps ahead short-term load forecasting of power system
10.1109/tia.2024.3375802 · 2024 · External reference
A novel deep multi-task learning model for spatial–temporal fault detection and diagnosis in industrial systems
10.1002/cjce.25760 · 2025 · External reference
A fault diagnosis data augmentation method integrating multimodal non-Gaussian denoising diffusion generative adversarial network
10.1016/j.aei.2025.103776 · 2025 · External reference
A novel solution for data uncertainty and insufficient in data-driven chiller fault diagnosis based on multi-modal data fusion
10.1016/j.enbuild.2024.115197 · 2025 · External reference
A novel data augmentation method based on denoising diffusion probabilistic model for fault diagnosis under imbalanced data
10.1109/tii.2024.3366991 · 2024 · External reference
Multi-mode data augmentation and fault diagnosis of rotating machinery using modified ACGAN designed with new framework
10.1016/j.aei.2022.101552 · 2022 · External reference
Ensemble data augmentation for imbalanced fault diagnosis
10.1109/tim.2023.3307757 · 2023 · External reference
IEVAEGAN: An input enhancement VAEGAN for rotating component fault diagnosis with extremely limited data
10.1109/jsen.2024.3476381 · 2024 · External reference
A global information-guided denoising diffusion probabilistic model for fault diagnosis with imbalanced data
10.1016/j.engappai.2025.110312 · 2025 · External reference
Rotating machinery fault-induced vibration signal modulation effects: A review with mechanisms, extraction methods and applications for diagnosis
10.1016/j.ymssp.2023.110489 · 2023 · External reference
CNN parameter design based on fault signal analysis and its application in bearing fault diagnosis
10.1016/j.aei.2023.101877 · 2023 · External reference
A survey of mamba
10.1145/3819582 · 2026 · External reference
A comprehensive survey and taxonomy of mamba: Applications, Challenges, and Future Directions
10.1016/j.inffus.2025.104094 · 2025 · External reference
Power load forecasting based on time-frequency domain feature fusion
10.1016/j.engappai.2026.114438 · 2026 · External reference
MF-Mamba: Multi-scale convolution and mamba fusion model for semantic segmentation of remote sensing imagery
10.1109/tgrs.2025.3593410 · 2025 · External reference
Multimodal unified generalization and translation network for intelligent fault diagnosis under dynamic environments
10.1016/j.engappai.2025.112559 · 2025 · External reference
10.20944/preprints202011.0571.v1
10.20944/preprints202011.0571.v1 · External reference
Runoff forecasting using convolutional neural networks and optimized bi-directional long short-term memory
10.1007/s11269-022-03414-8 · 2023 · External reference
Positional encoding in transformer-based time series models: A survey
10.1007/s13042-026-03151-z · 2026 · External reference
A novel deep multi-task learning model for spatial–temporal fault detection and diagnosis in industrial systems
10.1002/cjce.25760 · ExternalCitation · doi-reference
Runoff forecasting using convolutional neural networks and optimized bi-directional long short-term memory
10.1007/s11269-022-03414-8 · ExternalCitation · doi-reference
Positional encoding in transformer-based time series models: A survey
10.1007/s13042-026-03151-z · ExternalCitation · doi-reference
A review of data-driven machinery fault diagnosis using machine learning algorithms
10.1007/s42417-022-00498-9 · ExternalCitation · doi-reference
Multi-mode data augmentation and fault diagnosis of rotating machinery using modified ACGAN designed with new framework
10.1016/j.aei.2022.101552 · ExternalCitation · doi-reference
CNN parameter design based on fault signal analysis and its application in bearing fault diagnosis
10.1016/j.aei.2023.101877 · ExternalCitation · doi-reference
A fault diagnosis data augmentation method integrating multimodal non-Gaussian denoising diffusion generative adversarial network
10.1016/j.aei.2025.103776 · ExternalCitation · doi-reference
A novel solution for data uncertainty and insufficient in data-driven chiller fault diagnosis based on multi-modal data fusion
10.1016/j.enbuild.2024.115197 · ExternalCitation · doi-reference
A global information-guided denoising diffusion probabilistic model for fault diagnosis with imbalanced data
10.1016/j.engappai.2025.110312 · ExternalCitation · doi-reference
Multimodal unified generalization and translation network for intelligent fault diagnosis under dynamic environments
10.1016/j.engappai.2025.112559 · ExternalCitation · doi-reference
Power load forecasting based on time-frequency domain feature fusion
10.1016/j.engappai.2026.114438 · ExternalCitation · doi-reference
A comprehensive survey and taxonomy of mamba: Applications, Challenges, and Future Directions
10.1016/j.inffus.2025.104094 · ExternalCitation · doi-reference
Industrial intelligence and industrial structure change: Effect and mechanism
10.1016/j.iref.2024.04.002 · ExternalCitation · doi-reference
Long-term sequence dependency capture for spatiotemporal graph modeling
10.1016/j.knosys.2023.110818 · ExternalCitation · doi-reference
Global contextual residual convolutional neural networks for motor fault diagnosis under variable-speed conditions
10.1016/j.ress.2022.108618 · ExternalCitation · doi-reference
Rotating machinery fault-induced vibration signal modulation effects: A review with mechanisms, extraction methods and applications for diagnosis
10.1016/j.ymssp.2023.110489 · ExternalCitation · doi-reference
Industrial intelligence-driven production and operations management
10.1080/00207543.2023.2207956 · ExternalCitation · doi-reference
IEVAEGAN: An input enhancement VAEGAN for rotating component fault diagnosis with extremely limited data
10.1109/jsen.2024.3476381 · ExternalCitation · doi-reference
MF-Mamba: Multi-scale convolution and mamba fusion model for semantic segmentation of remote sensing imagery
10.1109/tgrs.2025.3593410 · ExternalCitation · doi-reference
Dynamic temporal dependency model for multiple steps ahead short-term load forecasting of power system
10.1109/tia.2024.3375802 · ExternalCitation · doi-reference
A novel data augmentation method based on denoising diffusion probabilistic model for fault diagnosis under imbalanced data
10.1109/tii.2024.3366991 · ExternalCitation · doi-reference
Multiscale residual attention convolutional neural network for bearing fault diagnosis
10.1109/tim.2022.3196742 · ExternalCitation · doi-reference
A novel local binary temporal convolutional neural network for bearing fault diagnosis
10.1109/tim.2023.3298653 · ExternalCitation · doi-reference
Ensemble data augmentation for imbalanced fault diagnosis
10.1109/tim.2023.3307757 · ExternalCitation · doi-reference
A survey of mamba
10.1145/3819582 · ExternalCitation · doi-reference
Extraction of local and global features by a convolutional neural network–long short-term memory network for diagnosing bearing faults
10.1177/09544062211016505 · ExternalCitation · doi-reference
10.20944/preprints202011.0571.v1
10.20944/preprints202011.0571.v1 · ExternalCitation · doi-reference
A convolutional neural network method based on Adam optimizer with power-exponential learning rate for bearing fault diagnosis
10.21595/jve.2022.22271 · ExternalCitation · doi-reference
10.3390/app15031389
10.3390/app15031389 · ExternalCitation · doi-reference
A review on vibration monitoring techniques for predictive maintenance of rotating machinery
10.3390/eng4030102 · ExternalCitation · doi-reference
10.3390/machines11070746
10.3390/machines11070746 · ExternalCitation · doi-reference
Intelligent fault diagnosis technology for mechanical equipment: Current status and development
10.63313/sd.2002 · ExternalCitation · doi-reference
