Quantitative analysis of dynamic safety-critical systems using temporal fault trees.
Emerging technological systems present complexities that pose new risks and hazards. Some of these systems, called safety-critical systems, can have very disastrous effects on human life and the environment if they fail. For this reason, such systems may feature multiple modes of operation, which may make use of redundant components, parallel ...
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Dynamic model-based safety analysis : from state machines to temporal fault trees.
Finite state transition models such as State Machines (SMs) have become a prevalent paradigm for the description of dynamic systems. Such models are well-suited to modelling the behaviour of complex systems, including in conditions of failure, and where the order in which failures and fault events occur can affect the overall outcome (e.g.
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IoT-Driven Robust Bearing Fault Diagnosis for Induction Motors Under Operating-Condition Shift. [PDF]
Kaya ŞM, Jobani AE.
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Internet of Things-Based Energy Consumption-Aware Framework Design for Smart Grid Environment. [PDF]
Çolak MA, Bayılmış C.
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Zhu Y, Yang Q.
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He Y, Lu Z, Deng Y, Wang D.
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A machine learning-based classification method for SynRM faults. [PDF]
Rajini V +6 more
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A transformer-XGBoost based model to fault diagnosis for CPR1000. [PDF]
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Hybrid quantum-classical neural networks for real-time fault detection in power systems. [PDF]
Hashmi H +7 more
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Multi-Source Aero-Engine Fault Diagnosis Using Explainable Boosted Tree with Spatiotemporal Attention and Adaptive Feature Selection. [PDF]
Zhou T +4 more
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