The carbon brushes and slip rings of a hydrogen-erator are the main components guiding the excitation current from the bridge to the rotor windings. The brushes' temperature are crucial to infer their operational ...
The carbon brushes and slip rings of a hydrogen-erator are the main components guiding the excitation current from the bridge to the rotor windings. The brushes' temperature are crucial to infer their operational condition and, the generator status. This work presents the temperature measurement of six Fiber Bragg Gratings (FBG) sensors installed in a 370 MVA electric generator brushes. The results show the sensors' capacity to monitor the brushes' temperature in accordance with the current flowing through them. Together with the sensors, an Artificial Intelligence (AI) technique was applied to the measured temperature to detect anomalous events regarding the current supplied to the rotor windings. The optical sensors combined with the AI could detect five events of abnormal current behaviour. One is presented in detail in this paper. This sensing system can be further applied to online fault detection using the temperature measured by the FBGs as a brush condition indicator and a generator operation and maintenance tool.
Normalizing flows have been successfully modeling a complex probability distribution as an invertible transformation of a simple base distribution. However, there are often applications that require more than invertib...
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This paper investigates the classification of low probability of intercept (LPI) radar signals by exploiting the intrinsic advantages of the Vision Transformer (ViT). Due to the characteristics of LPI radar signals, s...
This paper investigates the classification of low probability of intercept (LPI) radar signals by exploiting the intrinsic advantages of the Vision Transformer (ViT). Due to the characteristics of LPI radar signals, such as intrapulse modulation, wide frequency bands, and low transmission power, these signals are challenging to be detected and classified using traditional analytic methods. This has led to the adoption of various deep learning techniques to overcome these limitations. On the one hand, the ViT, originally developed for natural language processing, has demonstrated outstanding performance in computer vision by replacing the structure of the convolutional neural network (CNN) with the transformer, specifically leveraging self-attention. Therefore, this paper explores a method based on the ViT technique for classifying LPI signal images. The simulation results show that the proposed ViT method outperforms the traditional CNN method by 12.8% at −10dB SNR.
Test-time adaptation (TTA) addresses the unforeseen distribution shifts occurring during test time. In TTA, performance, memory consumption, and time consumption are crucial considerations. A recent diffusion-based TT...
This paper proposes a reconfiguration for a single-phase, double conversion uninterruptible power supply (UPS). With the addition of two static switches to the original circuit, the UPS mitigates the ripple in the cur...
This paper proposes a reconfiguration for a single-phase, double conversion uninterruptible power supply (UPS). With the addition of two static switches to the original circuit, the UPS mitigates the ripple in the current, through battery discharge performed by two legs. Other than these switches, the circuit topology is preserved. The preliminary results show a satisfactory level of ripples for the inductor current and suitable power quality for the output voltage.
This study examines the mapping of research data on digital technology in the field of health education using bibliometric analysis method. Data was collected by identifying keywords in the Scopus database and sorting...
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In this paper, a dual-channel converter with a positive output and negative voltage output is proposed. It integrates a positive voltage output converter and a negative voltage output converter, and shares the same sw...
In this paper, a dual-channel converter with a positive output and negative voltage output is proposed. It integrates a positive voltage output converter and a negative voltage output converter, and shares the same switches. The number of active components can be reduced. In addition, the circuit can achieve dual output voltage control with a single controller and PWM drive signal by appropriately designing the ratio of the number of windings of the coupling inductor. A regulated positive voltage output and negative voltage output can be achieved.
We propose a novel robust nonlinear $\mathcal{W}_{\infty}$ optimal control method for dynamical systems with nonaffine control inputs. The nonlinear $\mathcal{W}_{\infty}$ control formulation extends the classic n...
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ISBN:
(数字)9783907144107
ISBN:
(纸本)9798331540920
We propose a novel robust nonlinear
$\mathcal{W}_{\infty}$
optimal control method for dynamical systems with nonaffine control inputs. The nonlinear
$\mathcal{W}_{\infty}$
control formulation extends the classic nonlinear
$\mathcal{H}_{\infty}$
one, considering a weighted Sobolev norm of the cost variable. This approach assumes that the cost variable belongs to the weighted Sobolev space
$\mathcal{W}_{m,p,\mathbf{\Gamma}}$
, ensuring continuity and differentiability up to degree
$m$
in a certain domain
$\Omega$
. Consequently, in addition to the well-known features provided by the
$\mathcal{H}_{\infty}$
approach in terms of disturbance attenuation, the closed-loop system benefits from the enhanced transient performance. Here, the robust nonlinear
$\mathcal{W}_{\infty}$
optimal control problem is formulated via dynamic programming for increased-order systems, and a particular solution is proposed to the resulting Hamilton-Jacobi equation, along with the corresponding stability analysis. To validate the proposed method and its versatility, we provide numerical results for the control of a quadrotor. Additionally, leveraging the inherent
$\mathcal{L}_{2}$
-gain properties of our approach, we demonstrate that the resulting controller can achieve trajectory tracking with guaranteed asymptotic stability for the whole closed-loop system.
Education about health sciences has historically been limited in the curriculum of health professionals and largely inaccessible to the public. In practice, most of the health science education is still running conven...
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This paper presents a design to improve the robustness of visual SLAM(vSLAM). A processing step of feature-removal is added to the tracking thread of the conventional ORB-SLAM2 algorithm to improve the localization ac...
This paper presents a design to improve the robustness of visual SLAM(vSLAM). A processing step of feature-removal is added to the tracking thread of the conventional ORB-SLAM2 algorithm to improve the localization accuracy of a mobile robot in an environment with moving persons. Instance segmentation and motion tracking are intergrated to identify motion state of people in an image. ORB feature points belonging to moving persons are removed for further processing of the vSLAM pipeline. The advantage of this method is that the vSLAM can remove feature points of moving people, while retain those belonging to static people in the environment, which improves the accuracy of robot pose estimation. The improved ORB-SLAM2 algorithm has been implemented in a NVIDIA Xavier embedded system, which is integrated to a mobile robot. In practical robot navigation experiments, the average positioning error of the proposed method is within 4cm for 22.4m travel distance. Compared with conventional ORB-SLAM2, the average accuracy of our vSLAM method improves 97% in a dynamic environment with moving people.
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