Sliding sampling and successive variational mode decomposition CNN-BiLSTM-attention based fault detection and early warning method for DC microgrid. [PDF]
Sci RepDai Y, Wang M, Zhang L, Wang S, Jiang Z.
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Fault diagnosis of aero-engines using transfer dispersion entropy and dispersion patterns. [PDF]
PLoS OneZhang H, Zhang Y, Liu J, Dong K.
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Fine-tuned multimodal large language model for autonomous state cognition system of shape-recognition 6-bar tensegrity integrated with flexible sensors. [PDF]
Microsyst NanoengMao Z +9 more
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Diffusion-augmented YOLO26-Swin cascaded framework with hybrid SHAP-CAM for autonomous power grid inspection. [PDF]
Auton Intell SystStefenon SF +4 more
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A fault diagnosis method for complex systems based on hierarchical belief rule base with One-vs-Rest strategy. [PDF]
Sci RepWu J, Li N, Li Y, Lin L, Liu B.
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From Fault Classification to Fault Tolerance for Multi-Agent Systems
, 2013 Faults are a concern for Multi-Agent Systems (MAS) designers, especially if the MAS are built for industrial or military use because there must be some guarantee of dependability. Some fault classification exists for classical systems, and is used to define faults. When dependability is at stake, such fault classification may be used from the beginning
Katia Potiron +2 more
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Hierarchical Classification for Unknown Faults
2020 IEEE International Conference on Prognostics and Health Management (ICPHM), 2020Data-driven prognostics and health management (PHM) models are generally trained on a set of data collected from the system under study. A standard assumption of this paradigm is that the training data contains all the normal operating conditions and fault conditions that are possible.
Stephen C. Adams +4 more
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