Search Results (99)

The on-orbit geometric calibration accuracy of high-resolution space cameras directly affects the application value of Earth observation data. Conventional on-orbit geometric calibration methods primarily rely on ground calibration fields, making it difficult to simultaneously achieve high precision and real-time monitoring. To address this limitation, we, in collaboration with Tsinghua University, propose a high-precision, real-time, on-orbit geometric calibration system based on active optical monitoring. The proposed system employs reference lasers to integrate the space camera and the star tracker into a unified optical system, enabling real-time monitoring and correction of the camera’s exterior orientation parameters. However, during on-orbit operation, the space camera is subjected to a complex thermal environment, which induces thermal deformation of optical elements and their supporting structures, thereby degrading the measurement accuracy of the geometric calibration system. To address this issue, this article analyzes the impact of temperature fluctuations on the focal plane, the reference laser unit, and the laser relay folding unit and proposes athermalization design optimization schemes. Through the implementation of a thermal-compensated design for the collimation optical system, the pointing stability and divergence angle control of the reference laser are effectively enhanced. To address the thermal sensitivity of the laser relay folding unit, a right-angle cone mirror scheme is proposed, and its structural materials are optimized through thermo–mechanical–optical coupling analysis. Finite element analysis is conducted to evaluate the thermal stability of the on-orbit geometric calibration system, and the impact of temperature variations on measurement accuracy is quantified using an optical error assessment method. The results show that, under temperature fluctuations of 5 °C for the focal plane and the reference laser unit, 1 °C for the laser relay folding unit, and 2 °C for the star tracker, the maximum deviation of the system’s measurement reference does not exceed 0.57″ (3σ). This enables long-term, stable, high-precision monitoring of exterior orientation parameter variations and improves image positioning accuracy. Full article

Tabletop 3D display is an emerging display form that enables multiple users to share viewing around a central tabletop, making it promising for the application of collaborative work. However, achieving an ideal ring-shaped viewing zone with a large radial viewing angle remains a challenge for most current tabletop 3D displays. This paper presents a tabletop 3D display based on a panoramic annular lens array to realize a large radial viewing angle. Each panoramic annular lens in the array is designed with a block-structured panoramic front unit and a relay lens system, enabling the formation of a ring-shaped viewing zone and increasing the radial angle of the outgoing light. Additionally, the diffusion characteristics of the optical diffusing screen component are analyzed under large angles of incidence after light passes through the panoramic annular lens array. Then, a method for generating the corresponding elemental image array is presented. The results of the simulation experiments demonstrate that the viewing range is improved to −78.4–−42.2° and 42.6–78.9°, resulting in a total radial viewing angle of up to 72.5°, and the proposed 3D display can present a 360° viewable 3D image with correct perspective and parallax. Full article

In computational electromagnetics, the finite-difference time-domain (FDTD) method is recognized for its volumetric discretization approach. However, it can be computationally demanding when addressing large-scale electromagnetic problems. This paper introduces a novel approach by incorporating Graphic Process Units (GPUs) into an FDTD algorithm. It leverages the Compute Unified Device Architecture (CUDA) along with OpenMPI and the NVIDIA Collective Communications Library (NCCL) to establish a parallel scheme for the FDTD algorithm in distributed cluster GPUs. This approach enhances the computational efficiency of the FDTD algorithm by circumventing data relaying by the CPU and the limitations of the PCIe bus. The improved efficiency renders the FDTD algorithm a more practical and efficient solution for real-world electromagnetic problems. Full article

To achieve rapid distance estimation and tracking of moving targets in a large field of view, this paper proposes an innovative simulation method. Using a low-cost approach, the imaging and distance measurement performance of the designed cooling-type mid-wave infrared compound-eye camera (CM-CECam) is experimentally evaluated. The compound-eye camera consists of a small-lens array with a spherical shell, a relay optical system, and a cooling-type mid-wave infrared detector. Based on the spatial arrangement of the small-lens array, a precise simulation imaging model for the compound-eye camera is developed, constructing a virtual imaging space. Distance estimation and error analysis for virtual targets are performed using the principle of stereo disparity. This universal simulation method provides a foundation for spatial design and image-plane adjustments for compound-eye cameras with specialized structures. Using the raw images captured by the compound-eye camera, a scene-specific piecewise linear mapping method is applied. This method significantly reduces the brightness contrast differences between sub-images during wide-field observations, enhancing image details. For the fast detection of moving targets, ommatidia clusters are defined as the minimal spatial constraint units. Local information at the centers of these constraint units is prioritized for processing. This approach replaces traditional global detection methods, improving the efficiency of subsequent processing. Finally, the simulated distance measurement results are validated using real-world scene data. Full article

Distance protection is widely applied in AC transmission systems. It may operate incorrectly under power swings, so a power swing blocking unit (PSBU) is needed to work with the distance protection relay. Such a unit should not only block the protection relay in time when a power swing occurs, but also deblock the protection relay after detecting a fault during the power swing. In this paper, a method that satisfies these requirements is proposed. To discriminate between power swings and faults, the characteristics of three-phase voltage under a power swing and fault situation are used. Principal Component Analysis (PCA) is applied to extract and quantify the characteristics. To detect faults during power swings, an index is proposed, and the change rate of the index is used to form the criterion. Simulations for different kinds of power swing and fault situations are conducted based on a two-end system and a nine-bus system in PSCAD/EMTDC. The simulation test results indicate that the proposed method can block the protection relay reliably under a power swing and deblock the relay quickly after detecting a fault during the power swing. Moreover, the proposed method is compared with other methods. The comparison results show that the proposed method has an advantage in terms of response speed and is less affected by measurement noise. Full article

This paper proposes a novel polar coding scheme tailored for indoor visible light communication (VLC) systems. Simulation results demonstrate a significant reduction in bit error rate (BER) compared to uncoded transmission, with a coding gain of at least 5 dB. Furthermore, the reliable communication area of the VLC system is substantially extended. Building on this foundation, this study explores the joint design of polar codes and physical-layer network coding (PNC) for VLC systems. Simulation results illustrate that the BER of our scheme closely approaches that of the conventional VLC relay scheme. Moreover, our approach doubles the throughput, cuts equipment expenses in half, and boosts effective bit rates per unit time-slot twofold. This proposed design noticeably advances the performance of VLC systems and is particularly well-suited for scenarios with low-latency demands. Full article

Intentional controlled islanding (ICI) is a crucial strategy to avert power system collapse and blackouts caused by severe disturbances. This paper introduces an innovative IoT-based ICI strategy that identifies the optimal location for system segmentation during emergencies. Initially, the algorithm transmits essential data from phasor measurement units (PMUs) to the IoT cloud. Subsequently, it calculates the coherency index among all pairs of generators. Leveraging IoT technology increases system accessibility, enabling the real-time detection of changes in network topology post-disturbance and allowing the coherency index to adapt accordingly. A novel algorithm is then employed to group coherent generators based on relative coherency index values, eliminating the need to transfer data points elsewhere. The “where to island” subproblem is formulated as a mixed integer linear programming (MILP) model that aims to boost system transient stability by minimizing power flow interruptions in disconnected lines. The model incorporates constraints on generators’ coherency, island connectivity, and node exclusivity. The subsequent layer determines the optimal generation/load actions for each island to prevent system collapse post-separation. Signals from the IoT cloud are relayed to the circuit breakers at the terminals of the optimal cut-set to establish stable isolated islands. Additionally, controllable loads and generation controllers receive signals from the cloud to execute load and/or generation adjustments. The proposed system’s performance is assessed on the IEEE 39-bus system through time-domain simulations on DIgSILENT PowerFactory connected to the ThingSpeak cloud platform. The simulation results demonstrate the effectiveness of the proposed ICI strategy in boosting power system stability. Full article

Wind farms with type IV wind turbines from various manufacturers are being massively put into operation. These wind turbines comply with the requirements of the grid codes of the countries where they are designed and/or manufactured, but do not factor in the specific features of the distribution networks of other countries to which they are connected. The study at issue involves a comparative analysis of the requirements of grid codes of different countries for the stable operation of wind turbines under standard disturbances. The low voltage ride through (LVRT) characteristic makes it possible to prevent wind turbine shutdowns in case of short-term voltage dips of a given depth and duration. The calculations of transient processes indicate that wind turbines may not meet the requirements of the grid code of a particular country for their stable operation. As a result, standard disturbances will block the reactive current injection and the wind turbine will be switched off. This is often caused by the relay protection devices with a time delay of 1–2 s, which are used in distribution networks and implement the functions of long-range redundancy. Excessive shutdowns of wind turbines lead to emergency rises in the loads for the generating units of conventional power plants, aggravating the post-accident conditions and disconnecting consumers of electricity. This article presents a method for checking the LVRT characteristic settings for compliance with the technical requirements for wind turbines. To prevent wind turbine outages, one should either change the configuration of the LVRT characteristic, upgrade the relay protection devices in the distribution network adjacent to the wind farm, or implement group or individual technical solutions at the wind farm. The performance of the proposed technical solutions is confirmed by the calculations of transient processes. Full article

Phasor-domain (RMS) simulations have become increasingly vital in modern power system analysis, particularly as the complexity and scale of these systems have expanded with the integration of renewable energy sources. ePHASORSIM, an advanced phasor-based simulation tool developed by OPAL-RT, plays a crucial role in this context by enabling real-time phasor-domain simulation and hardware-in-the-loop testing. To keep pace with these evolving needs, continuous efforts are being made to further improve the accuracy, efficiency, and reliability of ePHASORSIM-based simulations. These efforts include automating model conversion processes for enhanced integration with ePHASORSIM, extending ePHASORSIM’s simulation range with custom models, developing hybrid co-simulation techniques involving ePHASORSIM and an EMT simulator, enhancing simulation scalability, and refining HIL testing to achieve more precise validation of control and protection systems. This paper provides a comprehensive review of these recent advances. Additionally, the paper discusses the conversion of models from PowerFactory—a widely used and comprehensive modeling environment—to ePHASORSIM through both automated tools and manual methods using Excel workbooks, which has been discussed little in the literature. Furthermore, as ePHASORSIM is a relatively new tool with limited cross-validation studies, the paper aims to contribute to this area by presenting a comparative validation against DIgSILENT PowerFactory, with a specific emphasis on its application in electric vehicle charging management systems. Full article

Compared to the AC counterpart, the DC shore power system provides a significant advantage of efficient power supply from renewable sources to ships and onshore loads. Super-capacitors serve as key energy storage units in such a system to buffer the power fluctuations and collect the regenerative energy. However, the ultra-wide voltage range of super-capacitors imposes a significant challenge in the topology selection and efficiency optimization of the interfacing isolated bidirectional DC–DC converter. To tackle this challenge, this paper analyzes and compares two promising converter topologies, which are a configurable modular two-level dual-active bridge (CM-2L-DAB) and a three-level dual-active bridge (3L-DAB). To facilitate an ultra-wide voltage range, extended phase-shift (EPS) modulation in conjunction with the topology reconfiguration is analyzed for the CM-2L-DAB, while a hybrid modulation scheme is proposed for the 3L-DAB. A unified design approach is provided for both topologies, which also yields to the power loss modeling. On this basis, the CM-2L-DAB and 3L-DAB are thoroughly compared in terms of the modulation schemes, current stress, soft-switching operation, power conversion efficiency, material usage, closed-loop control scheme, and reliability. A prominent conclusion can be drawn that the CM-2L-DAB provides a higher efficiency than the 3L-DAB over the whole voltage range, but it relies on additional relays to reconfigure its topology which results in lower reliability and dynamic performance than the 3L-DAB. Full article

When synthesizing systems for railway interlocking, it is recommended to use automated models to implement the logic of railway automation and remote control units. Finite-state machines (FSMs) can be implemented on any hardware component. When using relay technology, the functional safety of electrical interlocking is achieved by using uncontrolled (safety) relays with a high coefficient of asymmetry of failures in types 1 → 0 and 0 → 1. When using programmable components, the use of backup and diverse protection methods is required. This paper presents a flexible approach to synthesizing FSMs for railway automation and remote control units that offer both individual and route-based control. Unlike existing solutions, this proposal considers the pre-failure states of railway automation and remote control units during the finite-state machine synthesis stage. This enables the implementation of self-checking and self-diagnostic modules to manage automation units. By increasing the number of states for individual devices and considering the states of interconnected objects, the transition graphs can be expanded. This expansion allows for the synthesis of the transition graph of the control subsystem and other systems. The authors used a field-programmable gate array (FPGA) to implement a finite-state machine. In this case, the proposal is to encode the states of a finite-state machine using weight-based sum codes in the residue class ring based on a given modulus. The best coverage of errors occurring at the outputs of the logic converter in the structure of the FSM can be ensured by selecting the weighting coefficients and the value of the module. This paper presents an example of synthesizing an FPGA-based FSM using state encoding through modular weight-based sum codes. The operation of the synthesized device was modeled. It was found to operate according to the same algorithm as the real devices. When synthesizing self-checking and self-controlled train control devices, it is recommended to consider the solutions proposed in this paper. Full article

This study presents a numerical method for evaluating the maintainability of a dual-axis solar tracking system that can be deployed in residential areas for improved energy production. The purpose of this research manuscript is threefold. It targets the following objectives: (i) First, we present the construction of a self-sufficient dual-axis solar tracking system based on a low-power electronic schematic that requires only one motor driver to control the azimuth and elevation angles of the photovoltaic (PV) panel. The automated system’s main electronic equipment comprises 1 × Arduino Mega2560 microcontroller unit (MCU), 1 × TB6560 stepper driver module, 2 × stepper motors, 2 × relay modules, 1 × solar charge controller, 1 × accumulator, and 1 × voltage convertor. Additional hardware components such as photoresistors, mechanical limit switches, rotary encoders, voltage, and current sensors are also included to complete the automation cycle of the solar tracking system. (ii) Second, the Arduino Mega 2560 prototyping board is replaced by a custom-made and low-cost application-specific printed circuit board (ASPCB) based on the AVR controller. The MCU’s possible fault domain is then further defined by examining the risks of the poor manufacturing process, which can lead to stuck-at-0 (Sa0) and stuck-at-1 (Sa1) defects. Besides these issues, other challenges such as component modularity, installation accessibility, and hardware failures can affect the automated system’s serviceability. (iii) Third, we propose a novel set of maintenance-oriented metrics that combine the previously identified variables to provide a maintainability index (MI), which serves as a valuable tool for evaluating, optimizing, and maintaining complex systems such as solar tracking devices. The experimental data show that the computed MI improves the system’s maintainability and enhances repair operations, increasing uptime. Full article

Industry 4.0 has become one of the most dominant research areas in industrial science today. Many industrial machinery units do not have modern standards that allow for the use of image analysis techniques in their commissioning. Intelligent material handling, sorting, and object recognition are not possible with the machinery we have. We therefore propose a novel deep learning approach for existing robotic devices that can be applied to future robots without modification. In the implementation, 3D CAD models of the PCB relay modules to be recognized are also designed for the implantation machine. Alternatively, we developed and manufactured parts for the assembly of aluminum profiles using FDM 3D printing technology, specifically for sorting purposes. We also apply deep learning algorithms based on the 3D CAD models to generate a dataset of objects for categorization using CGI rendering. We generate two datasets and apply image-to-image translation techniques to train deep learning algorithms. The synthesis achieved sufficient information content and quality in the synthesized images to train deep learning algorithms efficiently with them. As a result, we propose a dataset translation method that is suitable for situations in which regenerating the original dataset can be challenging. The results obtained are analyzed and evaluated for the dataset. Full article

The kidney injury molecule (KIM)-1 is shed from proximal tubular cells in acute kidney injury (AKI), relaying tubular epithelial proliferation. Additionally, KIM-1 portends complex immunoregulation and is elevated after exposure to lipopolysaccharides. It thus may represent a biomarker in critical illness, sepsis, and sepsis-associated AKI (SA-AKI). To characterise and compare KIM-1 in these settings, we analysed KIM-1 serum concentrations in 192 critically ill patients admitted to the intensive care unit. Irrespective of kidney dysfunction, KIM-1 serum levels were significantly higher in patients with sepsis compared with other critical illnesses (191.6 vs. 132.2 pg/mL, p = 0.019) and were highest in patients with urogenital sepsis, followed by liver failure. Furthermore, KIM-1 levels were significantly elevated in critically ill patients who developed AKI within 48 h (273.3 vs. 125.8 pg/mL, p = 0.026) or later received renal replacement therapy (RRT) (299.7 vs. 146.3 pg/mL, p < 0.001). KIM-1 correlated with markers of renal function, inflammatory parameters, hematopoietic function, and cholangiocellular injury. Among subcomponents of the SOFA score, KIM-1 was elevated in patients with hyperbilirubinaemia (>2 mg/dL, p < 0.001) and thrombocytopenia (<150/nL, p = 0.018). In univariate and multivariate regression analyses, KIM-1 predicted sepsis, the need for RRT, and multi-organ dysfunction (MOD, SOFA > 12 and APACHE II ≥ 20) on the day of admission, adjusting for relevant comorbidities, bilirubin, and platelet count. Additionally, KIM-1 in multivariate regression was able to predict sepsis in patients without prior (CKD) or present (AKI) kidney injury. Our study suggests that next to its established role as a biomarker in kidney dysfunction, KIM-1 is associated with sepsis, biliary injury, and critical illness severity. It thus may offer aid for risk stratification in these patients. Full article

In response to the challenges introduced by global warming and increased eutrophication, this paper presents an innovative modeling and simulation (M&S)-driven model for developing an automated inland water monitoring system. This system is grounded in a layered Internet of Things (IoT) architecture and seamlessly integrates cloud, fog, and edge computing to enable sophisticated, real-time environmental surveillance and prediction of harmful algal and cyanobacterial blooms (HACBs). Utilizing autonomous boats as mobile data collection units within the edge layer, the system efficiently tracks algae and cyanobacteria proliferation and relays critical data upward through the architecture. These data feed into advanced inference models within the cloud layer, which inform predictive algorithms in the fog layer, orchestrating subsequent data-gathering missions. This paper also details a complete development environment that facilitates the system lifecycle from concept to deployment. The modular design is powered by Discrete Event System Specification (DEVS) and offers unparalleled adaptability, allowing developers to simulate, validate, and deploy modules incrementally and cutting across traditional developmental phases. Full article