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A roadmap to fault diagnosis of industrial machines via machine learning: a brief review
In fault diagnosis, machine learning theories are gaining popularity as they proved to be an
efficient tool that not only reduces human effort but also identifies the health conditions of the …
efficient tool that not only reduces human effort but also identifies the health conditions of the …
Analysing Recent Breakthroughs in Fault Diagnosis through Sensor: A Comprehensive Overview.
Sensors, vital elements in data acquisition systems, play a crucial role in various industries.
However, their exposure to harsh operating conditions makes them vulnerable to faults that …
However, their exposure to harsh operating conditions makes them vulnerable to faults that …
Information-based Gradient enhanced Causal Learning Graph Neural Network for fault diagnosis of complex industrial processes
By representing the embedded components and their interactions in industrial systems as
nodes and edges in a graph, Graph Neural Networks (GNNs) have achieved outstanding …
nodes and edges in a graph, Graph Neural Networks (GNNs) have achieved outstanding …
A Hybrid Real-Time Framework for Efficient Fussell-Vesely Importance Evaluation Using Virtual Fault Trees and Graph Neural Networks
The Fussell-Vesely Importance (FV) reflects the potential impact of a basic event on system
failure, and is crucial for ensuring system reliability. However, traditional methods for …
failure, and is crucial for ensuring system reliability. However, traditional methods for …
Sliding window-aided recursive efficient kernel decomposition for KPI-oriented fault detection of complex industrial processes
H Ma, Y Wang, X Liu, J Yuan, Y Zhou - Knowledge-Based Systems, 2025 - Elsevier
Sliding window techniques are widely used for precise real-time fault detection. However,
their adoption increases the computational load, prompting integration with recursive …
their adoption increases the computational load, prompting integration with recursive …
HebCGNN: Hebbian-enabled causal classification integrating dynamic impact valuing
Classifying graph-structured data presents significant challenges due to the diverse features
of nodes and edges and their complex relationships. While Graph Neural Networks (GNNs) …
of nodes and edges and their complex relationships. While Graph Neural Networks (GNNs) …
Causality-guided fault diagnosis under visual interference in fused deposition modeling
Fused deposition modeling (FDM) is one of the additive manufacturing (AM) technologies
widely used in various industrial fields. Several factors can affect the manufacturing process …
widely used in various industrial fields. Several factors can affect the manufacturing process …
Out-of-Distribution Fault Diagnosis of Industrial Cyber-physical Systems Based on Orthogonal Anchor Clustering with Adaptive Balance
Given the critical role of rotating machinery in industrial cyber-physical systems (ICPS),
ensuring their reliable operation is essential for the stability and safety of ICPS. Deep neural …
ensuring their reliable operation is essential for the stability and safety of ICPS. Deep neural …
Casual inference-enabled graph neural networks for generalized fault diagnosis in industrial IoT system
Z Zhang, Q Li, S Liu, Z Zhang, W Chen, L Tang - Information Sciences, 2025 - Elsevier
Data-driven fault diagnosis plays a crucial role in diagnosing the operational status within
the Industrial Internet of Things (IIoT) systems. Although Graph Neural Networks (GNNs) …
the Industrial Internet of Things (IIoT) systems. Although Graph Neural Networks (GNNs) …
Multi large language model collaboration framework for few-shot link prediction in evolutionary fault diagnosis event graphs
T Wang, P Wang, F Yang, S Wang, Q Fang… - Journal of Process …, 2025 - Elsevier
Fault-tolerant control is crucial for ensuring flight safety in aircraft. However, existing
methods for fault diagnosis in nonlinear systems face challenges such as data sparsity …
methods for fault diagnosis in nonlinear systems face challenges such as data sparsity …