Sleep spindles are key reference signals in electroencephalography (EEG), typically occurring during non-rapid eye movement sleep. This study evaluates an automated detection method based on image-level analysis using an advanced vision transformer. A novel deep network, SpindleSwin-Net, is proposed for end-to-end and flexible sleep spindle detection by integrating the advantages of wavelet decomposition and the Swin Transformer architecture. The Montreal Archive of Sleep Studies (MASS) and DREAMS datasets are utilised. During image transformation, 1.5 s time–frequency maps containing annotated spindles are generated using a designed continuous wavelet transform filter, while randomly sampled EEG segments without annotations are labelled as non-spindles. In the detection stage, all time–frequency maps are input into a dual-branch Swin Transformer network to classify spindle versus non-spindle signals and to predict coordinates. Five-fold cross-validation is applied during training. SpindleSwin-Net is evaluated through both single-dataset and cross-dataset analyses. The method achieves recall, precision, F1-score, and IoU of (E1: 0.71, 0.62, 0.65, 0.66; E2: 0.99, 0.92, 0.95, 0.67) on the MASS dataset and (E3: 0.84, 0.52, 0.63, 0.60; E4: 0.88, 0.69, 0.77, 0.77) on the DREAMS dataset. Cross-dataset experiments demonstrate F1-scores of 0.96 and 0.63 on MASS and DREAMS, respectively. This vision transformer-based approach bypasses the cumbersome steps of conventional signal processing and reduces annotation time, offering potential as a practical tool to alleviate the workload of sleep clinicians.
Groundwater-induced internal erosion of finer soil fractions is critical for initiating granular slope collapse, but developing accurate computational models to capture coupled unsaturated seepage, particle migration, and hydro-mechanical property evolution of soils remains challenging. This study proposes a novel three-phase five-component mathematical model based on mixture theory to describe multiphysics phenomena in seepage-induced erosion in gap-graded granular soils. To enhance model accuracy, an improved micromechanics-based multiscale model is integrated to account for the specific moisture content and grading-dependent mechanical behavior of the porous medium experiencing seepage erosion. The computational framework innovatively employs an enhanced stabilized finite element method to eliminate numerical oscillations, validated via comparison with analytical solutions. The spatio-temporal evolution of the eroded zone and hydro-mechanical response of a reconstituted flume slope were successfully identified. Numerical results show volumetric settlements and shear sliding are major consequences of internal erosion, with soil property degradation near the slope toe accelerating failure. Neglecting internal erosion delays predicted failure onset and underestimates collapse severity. The proposed framework proves efficient and reliable for predicting seepage-induced slope failure initiation.
Multi-phase permanent magnet synchronous generators (PMSGs) are increasingly adopted in renewable energy systems and isolated microgrids due to their improved fault tolerance, reduced per-phase current stress, and enhanced power density compared to conventional three-phase machines. This article presents a systematic performance comparison between 15-phase and 9-phase PMSGs under four distinct operating conditions: healthy mode, single-phase open-circuit fault (Phase 1), and two fault-tolerant control (FTC) strategies. The first FTC technique involves opening a second phase with approximately 90-degree phase displacement from the faulty phase to attenuate power oscillations and reduce current amplitude imbalances. The second technique involves isolating a complete three-phase set containing the faulty phase without adapting the machine model. Both machines are modeled using the vector space decomposition (VSD) approach under field-oriented control (FOC), and simulations are performed in MATLAB/Simulink. Performance metrics include power efficiency, power losses, power ripple factor, electromagnetic power ripple, stator RMS current evolution, and stator current balance. Results demonstrate that the 15-phase PMSG consistently exhibits lower power ripple (6.5% vs. 15.54% under open-circuit fault), higher efficiency (89.02% vs. 87.44%), and reduced power losses across all fault scenarios. The first fault-tolerant strategy improves performance in both machines but is more effective in the 15-phase configuration. To validate the findings beyond offline simulation, hardware-in-the-loop (HIL) experiments are conducted on an OPAL-RT real-time platform, where the complete system—the PMSG and converter models together with the FOC and fault-tolerant control algorithms—is implemented within its FPGA framework. The HIL results for electromagnetic power and d–q axis stator currents show close agreement with the MATLAB/Simulink results across all operating conditions, confirming the FPGA implementability of the proposed control strategies under real-time constraints. These findings provide actionable insights for the design and control of high-phase-count generators in grid-connected and isolated power systems.
When equipped with a Wind Propulsion System (WPS), a ship motion includes a side velocity (drift) which is due to the aerodynamic side force generated by the WPS. This effect generates an additional resistance (sail-induced resistance) which must be evaluated to determine the net propulsive force of the WPS. The aerodynamic side force is also responsible for an increase in heel and rudder angles, which must also be evaluated to ensure that they do not exceed operational limits. In this study, these aspects are investigated for two vessels - the KVLCC2 (tanker) and the KCS (containership) - assuming they are retrofitted with a WPS. Numerical models of the ships were implemented in a ship simulator. First, following the method described by Kramer and Steen (2022), sail-induced resistance, heel angle and rudder angle are investigated using a technology-agnostic approach which consists in modelling the WPS force by a constant aerodynamic side force. It is shown that the KCS is considerably more affected by the presence of a WPS than the KVLCC2. The rudder is identified as the main contributor to the sail-induced resistance. Reducing ship speed, moving forward or downer the centre of effort of the WPS side force is shown to mitigate the impact of the WPS on the ship. Finally, the range of aerodynamic side force that can be expected for these ships is estimated based on statistical wind data and considering a rotor sail technology. Results show that the aerodynamic side force is negligible for both ships. wind propulsion; sail-induced resistance; 4 DOF; KCS; KVLCC2; rotor sail
