ArticleScientific reports2024
Elevator fault diagnosis based on digital twin and PINNs-e-RGCN.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Physics-Informed Neural Network-Based Elevator Degradation Diagnosis and Early Warning.Sensors (Basel, Switzerland) · 2026Article
- A graph-based evaluation framework for smart disaster response systems using IoT design quality metrics.Scientific reports · 2026Article
- A digital twin-assisted fault diagnosis method for stage lifts based on lightweight multi-scale convolution and broadcast self-attention mechanisms.Scientific reports · 2026Article
- Hybrid meta heuristic and fuzzy impedance method for fast fault location in power system lines.Scientific reports · 2026Article
- Development of Rule-Based Diagnostic Automation Technology for Elevator Fault Diagnosis.Sensors (Basel, Switzerland) · 2025Article
- SAL-YOLO-DeepSeek: a lightweight real-time detection and LLM-driven decision framework for intelligent escalator safety monitoring.Scientific reports · 2025Article
- A transformer guided multi modal learning framework for predictive and causal assessment of thermal runaway in high energy batteries.Scientific reports · 2025Article
- Adaptive neural network based leader-following consensus control for a class of second-order nonlinear multi-agent systems.Scientific reports · 2025Article
- Research on digital twin diagnosis model for the thermal-electric field of high-voltage switchgears.Scientific reports · 2025Article
- Remaining useful life prediction of lithium-ion batteries via spatial attention TLSTM and dilated CNN with evolutionary optimization.Scientific reports · 2025Article
- A novel and secure artificial intelligence enabled zero trust intrusion detection in industrial internet of things architecture.Scientific reports · 2025Article
- Bearing fault diagnosis for variable operating conditions based on KAN convolution and dual branch fusion attention.Scientific reports · 2025Article
- Machine Learning-Based Predictive Maintenance at Smart Ports Using IoT Sensor Data.Sensors (Basel, Switzerland) · 2025Article
- An adaptive hierarchical hybrid kernel ELM optimized by aquila optimizer algorithm for bearing fault diagnosis.Scientific reports · 2025Article
- Machine learning based fault classification for improved induction motor performance.PloS one · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
The rapid development of urbanization has led to a continuous rise in number of elevators. This has led to elevator failures from time to time. At present, although there are some studies on elevator fault diagnosis, they are more or less limited by the lack of data to make the research more superficial. For such complex special equipment as elevator, it is difficult to obtain reliable and sufficient data to train the fault diagnosis model. To address this issue, this paper first establishes a numerical model of vertical vibration for elevators with three degrees of freedom. The obtained motion equations are then used as constraints to acquire simulated vibration data through PINNs. Next, the proposed e-RGCN is employed for elevator fault diagnosis. Finally, experimental validation shows that the fault diagnosis accuracy with the participation of digital twins exceeds 90%, and the accuracy of the proposed model reaches 96.61%, significantly higher than that of other comparative models.
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