A 1270 Hz resonance occurred between ±350 kV/ 1000 MW Luxi back-to-back voltage source converter based high-voltage dc transmission (VSC-HVDC) converter and the 525 kV ac grid after disconnection of ...several ac transmission lines. To understand the resonance and find a solution, the impedance-based stability analysis model considering different equipment is first established. Then, the resonance is analyzed and repeated in the simulation based on the established model. The system stability can be judged by the ratio of grid impedance to the equivalent impedance of all parallel-connected equipment with the converter. To evaluate the occurrence and risk of resonance, the frequency range where the impedance has a negative-real-part has been searched and studied. In order to narrow the negative-real-part region to avoid potential resonance, solutions such as control strategy improvement and passive or active impedance adapter may be applicable and are discussed. For a complex system containing various equipment, the equipment can be divided into several subsectors to avoid modeling all possible combinations of equipment, which can be exhausting. And analysis has shown sufficient but not necessary condition to stabilize the system is to avoid the negative-real-part region in each sector.
Modular multilevel converters (MMC) are considered a top converter alternative for voltage-source converter (VSC) high-voltage, direct current (HVDC) applications. Main circuit design and converter ...performance evaluation are always important issues to consider before installing a VSC-HVDC system. Investigation into a steady-state analysis method for an MMC-based VSC-HVDC system is necessary. This paper finds a circular interaction among the electrical quantities in an MMC. Through this circular interaction, a key equation can be established to solve the unknown circulating current. A new steady-state model is developed to simply and accurately describe the explicit analytical expressions for various voltage and current quantities in an MMC. The accuracy of the expressions is improved by the consideration of the circulating current when deriving all the analytical expressions. The model's simplicity is demonstrated by having only one key equation to solve. Based on the analytical expressions for the arm voltages, the equivalent circuits for MMC are proposed to improve the current understanding of the operation of MMC. The feasibility and accuracy of the proposed method are verified by comparing its results with the simulation and experimental results.
A high-voltage direct current system using modular multilevel converter (MMC-HVDC) is a potential candidate for grid integration of renewable energy over long distances. The dc-link fault is an issue ...MMC-HVDC must deal with, especially for the nonpermanent faults when using overhead lines. This paper proposed a protection scheme to implement fast fault clearance and automatic recovery for nonpermanent faults on dc lines. By employing double thyristor switches, the freewheeling effect of diodes is eliminated and the dc-link fault current is allowed to freely decay to zero. Then, the dc arc can be naturally extinguished and the insulation on the short-circuit point can be restored. The thyristor switches convert the dc-link fault into an ac short circuit of the ac grid through MMC arms. The ac short-circuit current can be cleared simply by turning off all thyristor switches. Since circuit breakers are not tripped during fault clearance, MMC can immediately and automatically rebuild the dc-link voltage and restart power transmission. Simulation results using PSCAD/EMTDC have verified the validity of the proposed protection scheme.
Estimating accurate 3D hand pose from a single RGB image is a highly challenging problem in pose estimation due to self-geometric ambiguities, self-occlusions, and the absence of depth information. ...To this end, a novel Five-Layer Ensemble CNN (5LENet) is proposed based on hierarchical thinking, which is designed to decompose the hand pose estimation task into five single-finger pose estimation sub-tasks. Then, the sub-task estimation results are fused to estimate full 3D hand pose. The hierarchical method is of great benefit to extract deeper and better finger feature information, which can effectively improve the estimation accuracy of 3D hand pose. In addition, we also build a hand model with the center of the palm (represented as Palm) connected to the middle finger according to the topological structure of hand, which can further boost the performance of 3D hand pose estimation. Additionally, extensive quantitative and qualitative results on two public datasets demonstrate the effectiveness of 5LENet, yielding new state-of-the-art 3D estimation accuracy, which is superior to most advanced estimation methods.
This work addresses the problem of the estimator design for the periodic neural networks with polytopic uncertain connection weight matrices. The polytopic uncertainty is used to model the uncertain ...weight matrices. Bernoulli processes are employed to characterise the randomly occurred sensor nonlinearities, where the sensors are distributed in a large area. A Lyapunov function which depends both on the polytopic vertices and the period is constructed to improve the performance of the estimator. Sufficient conditions of the stochastic stability with $H_\infty $H∞ performance for the augmented system are established, and the corresponding gains of the estimator are designed. Finally, an illustrative numerical example is given.
This study adopts the method of third-order harmonic voltage injection (THVI) to move the peak value of a reference voltage toward the high capacitor voltage and increase the utilization rate of the ...capacitor voltage. This method can lower the cost or enlarge the capacity of a modular multilevel converter (MMC) when applied in high-voltage direct-current transmission. In this paper, the principle of THVI is introduced. Two calculation methods for modulation waves are studied, and the mathematical expressions of the capacitor voltage under all operating conditions are deduced. Thus, the optimal magnitude and phase of the third-order harmonic voltage are determined under all operating conditions. The mathematical expressions of the optimal magnitude and phase of the third-order harmonic voltage are obtained, and their online calculation burden is reduced. Simulation and experimental results show that the proposed method of THVI is feasible and effective.
In recent years, Graph Neural Networks (GNNs) based on deep learning techniques have achieved promising results in EEG-based depression detection tasks but still have some limitations. Firstly, most ...existing GNN-based methods use pre-computed graph adjacency matrices, which ignore the differences in brain networks between individuals. Additionally, methods based on graph-structured data do not consider the temporal dependency information of brain networks. To address these issues, we propose a deep learning algorithm that explores adaptive graph topologies and temporal graph networks for EEG-based depression detection. Specifically, we designed an Adaptive Graph Topology Generation (AGTG) module that can adaptively model the real-time connectivity of the brain networks, revealing differences between individuals. In addition, we designed a Graph Convolutional Gated Recurrent Unit (GCGRU) module to capture the temporal dynamical changes of brain networks. To further explore the differential features between depressed and healthy individuals, we adopt Graph Topology-based Max-Pooling (GTMP) module to extract graph representation vectors accurately. We conduct a comparative analysis with several advanced algorithms on both public and our own datasets. The results reveal that our final model achieves the highest Area Under the Receiver Operating Characteristic Curve (AUROC) on both datasets, with values of 83% and 99%, respectively. Furthermore, we perform extensive validation experiments demonstrating our proposed method's effectiveness and advantages. Finally, we present a comprehensive discussion on the differences in brain networks between healthy and depressed individuals based on the outputs of our final model's AGTG and GTMP modules.
In this paper, the finite-time cluster synchronization problem is addressed for complex dynamical networks (CDNs) with cluster characteristics under false data injection (FDI) attacks. A type of FDI ...attack is taken into consideration to reflect the data manipulation that controllers in CDNs may suffer. In order to improve the synchronization effect while reducing the control cost, a new periodic secure control (PSC) strategy is proposed in which the set of pinning nodes changes periodically. The aim of this paper is to derive the gains of the periodic secure controller such that the synchronization error of the CDN remains at a certain threshold in finite time with the presence of external disturbances and false control signals simultaneously. Through considering the periodic characteristics of PSC, a sufficient condition is obtained to guarantee the desired cluster synchronization performance, based on which the gains of the periodic cluster synchronization controllers are acquired by resolving an optimization problem proposed in this paper. A numerical case is carried out to validate the cluster synchronization performance of the PSC strategy under cyber attacks.
Automatic human fall detection is one important research topic in caring for vulnerable people, such as elders at home and patients in medical places. Over the past decade, numerous methods aiming at ...solving the problem were proposed. However, the existing methods only focus on detecting human themselves and cannot work effectively in complicated environments, especially for the falls on furniture. To alleviate this problem, a new method for human fall detection on furniture using scene analysis based on deep learning and activity characteristics is presented in this paper. The proposed method first performs scene analysis using a deep learning method faster R-CNN to detect human and furniture. Meanwhile, the space relation between human and furniture is detected. The activity characteristics of the detected people, such as human shape aspect ratio, centroid, motion speed are detected and tracked. Through measuring the changes of these characteristics and judging the relations between the people and furniture nearby, the falls on furniture can be effectively detected. Experiment results demonstrated that our approach not only accurately and effectively detected falls on furniture, such as sofa and chairs but also distinguished them from other fall-like activities, such as sitting or lying down, while the existing methods have difficulties to handle these. In our experiments, our algorithm achieved 94.44% precision, 94.95% recall, and 95.50% accuracy. The proposed method can be potentially used and integrated as a medical assistance in health care and medical places and appliances.
Abstract
With the increase in extremely low birth weight (ELBW) infants, their outcome attracted worldwide attention. However, in China, the related studies are rare. The hospitalized records of ELBW ...infants discharged from twenty-six neonatal intensive care units in Guangdong Province of China during 2008–2017 were analyzed. A total of 2575 ELBW infants were enrolled and the overall survival rate was 55.11%. From 2008 to 2017, the number of ELBW infants increased rapidly from 91 to 466, and the survival rate improved steadily from 41.76% to 62.02%. Increased survival is closely related to birth weight (BW), regional economic development, and specialized hospital. The incidence of complications was neonatal respiratory distress syndrome (85.2%), oxygen dependency at 28 days (63.7%), retinopathy of prematurity (39.3%), intraventricular hemorrhage (29.4%), necrotizing enterocolitis (12.0%), and periventricular leukomalacia (8.0%). Among the 1156 nonsurvivors, 90.0% of infants died during the neonatal period (≤ 28 days). A total of 768 ELBW infants died after treatment withdrawal, for reasons of economic and/or poor outcome. The number of ELBW infants is increasing in Guangdong Province of China, and the overall survival rate is improving steadily.
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