Search Results (5,670)

A novel partial discharge (PD) source localization method was proposed based on the traditional time difference in arrival (TDOA) method. Specifically, the non-line-of-sight (NLOS) propagation phenomenon of the ultra-high-frequency (UHF) signal was considered, and the NLOS propagation error was approximately replaced by a constant, thereby limiting the effect of NLOS propagation. Moreover, the strategy of utilizing more than four sensors was adopted to reduce the possible effect of overcorrection on NLOS propagation. In this paper, the derivation and implementation process of the proposed method is introduced from the perspectives of mathematical model and geometrical model, and its localization results were compared with the traditional TDOA method through an experimental study. The results showed that the speed of error increase of the traditional method presented faster, and the increment of sensor number helped to improve the localization accuracy, but the reduction in localization error becomes insignificant when the sensors exceed six. Finally, the experimental verifications were conducted based on a 35 kV testing transformer with six sensor installations. The experiments found that the proposed localization method had a better calculated accuracy and stability; the obtained minimum calculated error was 10.88 cm, the calculated accuracy can be improved by 82.04% and 78.94%, respectively, with six sensors than four and five sensors arrangement. Full article

Curved prisms can serve as core components of dispersive spectroscopy and converge light paths, making them widely used in spectral imaging technology. Their positional stability, surface shape errors, and temperature stability in optical systems directly affect the performance of spectral imaging systems. On the basis of the analysis of design indicators and optimization of the support structure for curved prisms, a multipoint flexible adhesive support structure (MPPASS) of large rectangular curved prisms for space-based application is proposed. The novelty of the MPPASS lies in its ability to achieve micro-stress and high stability support for large-aperture rectangular optical elements through the bonding of peripheral small points and the introduction of flexible bonding rings. The design principles of the adhesive support structure were deeply studied, and on this basis, the engineering design, finite element analysis, adhesive testing, and mechanical testing of large curved prisms were completed. The designed curved prism assembly has a maximum deformation displacement of 0.0085 mm and a maximum tilt angle of 0.65” under gravity loading, a first-order frequency of 1003.5 Hz, and a maximum acceleration amplification factor of 3.12 in the X, Y, and Z directions. The root mean square (RMS) variation value of the mirror shape errors for the curved prism assembly was 5.26 nm under a uniform temperature load of 20 ± 1 °C, and the RMS value of the mirror shape errors was 0.019 λ after mechanical testing. The installation surface flatness of 0.02 mm did not significantly affect its mirror shape errors. The experimental results verified the rationality of the design, temperature stability, and mechanical stability of the MPPASS. Full article

Coastal erosion is a growing concern in the Mediterranean region, where the combined effects of anthropogenic pressure, reduced fluvial sediment supply, and climate change-driven sea level rise and extreme storm events threaten the stability of sandy shorelines. This study examines the geomorphological impacts of the exceptional storm surge of 3 November 2023, associated with Storm Ciaran, which affected a vulnerable coastal segment north of the Morto Nuovo River in northern Tuscany (Italy). Using UAV-based photogrammetric surveys and high-resolution morphological analysis, we quantified shoreline retreat, dune toe regression, beach slope changes, and sediment volume loss. The storm induced an average shoreline retreat of over 5 m, with local peaks reaching 30 m, and a dune toe setback of up to 7 m. A net sediment budget deficit of approximately 1800 m³ was recorded, over 50% of the total volume added during soft nourishment interventions performed in the previous decade. Our findings highlight how a single high-energy event can match or exceed the annual average erosion rate, emphasizing the limitations of traditional shoreline-based monitoring and hard defense structures. This study highlights the importance of frequent, high-resolution monitoring focused on individual storm events, which is crucial to better understand their specific geomorphological impacts. Such detailed analyses help clarify whether long-term erosion trends are primarily driven by the cumulative effect of high-energy events. This knowledge is essential for identifying the most effective coastal protection strategies and for improving the design of defense structures. This approach is particularly relevant in the context of climate change, which is expected to increase the frequency and intensity of extreme events, making it imperative to base future planning on accurate, event-driven data. Full article

The oscillations induced by voltage source converters (VSCs) in DC voltage timescale dynamics pose significant challenges to the safe and stable operation of VSC-dominated power systems. However, previous studies have conducted simplified analyses without fully understanding the fundamental roles of different timescale control loops in converter-interfaced systems. In light of this, this study first identifies the key state variables and operating points that directly characterize the energy storage levels of devices and networks in AC systems. A model for the converter-interfaced system is then established in the specified DC voltage timescale. The key contribution of this work is the proposal of an analytical framework that decomposes system stability into self-stabilizing (Self-stable) and externally coupled stabilizing (En-stable) paths based on internal voltage amplitude and frequency, aiming to reveal the physical mechanisms behind internal voltage amplitude and frequency oscillations in DC voltage timescale dynamics. Based on this framework, the Self-stable path and En-stable path of the internal voltage amplitude/frequency of converter-interfaced systems are derived. This novel analytical method mathematically decouples the stability of a single variable into a direct self-influence path and an indirect path coupled through other system variables. Subsequently, the causes of internal voltage amplitude/frequency oscillations in the specified voltage timescale are explained using the Self-stability and En-stability analysis method. A key finding of this study is that the stability of the internal voltage amplitude and frequency exhibits a dual relationship: for amplitude stability, the Self-stable path is stabilizing, whereas the coupled path is destabilizing; for frequency stability, the roles are reversed. Finally, the results are verified through simulations. Full article

Accurate and automated detection of diseases is crucial for sustainable strawberry production. However, the challenges posed by small size, mutual occlusion, and high intra-class variance of symptoms in complex agricultural environments make this difficult. Mainstream deep learning detectors often do not perform well under these demanding conditions. We propose a novel detection framework designed for superior accuracy and robustness to address this critical gap. Our framework introduces four key innovations: First, we propose a novel attention-driven detection head featuring our Parallel Pyramid Attention (PPA) module. Inspired by pyramid attention principles, our module’s unique parallel multi-branch architecture is designed to overcome the limitations of serial processing. It simultaneously integrates global, local, and serial features to generate a fine-grained attention map, significantly improving the model’s focus on targets of varying scales. Second, we enhance the core feature fusion blocks by integrating Monte Carlo Attention (MCAttn), effectively empowering the model to recognize targets across diverse scales. Third, to improve the feature representation capacity of the backbone without increasing the parametric overhead, we replace standard convolutions with Frequency-Dynamic Convolutions (FDConv). This approach constructs highly diverse kernels in the frequency domain. Finally, we employ the Scale-Decoupled Loss function to optimize training dynamics. By adaptively re-weighting the localization and scale losses based on target size, we stabilize the training process and improve the Precision of bounding box regression for small objects. Extensive experiments on a challenging dataset related to strawberry diseases demonstrate that our proposed model achieves a mean Average Precision (MAP) of 81.1%. This represents an improvement of 2.1% over the strong YOLOv12-n baseline, highlighting its practical value as an effective tool for intelligent disease protection. Full article

Combustion instability poses a significant challenge in aerospace propulsion systems, particularly in afterburners that employ bluff-body flame stabilizers. The flame transfer function (FTF) is essential for characterizing the dynamic response of flames to perturbations, which is critical for predicting and controlling these instabilities. This study experimentally investigates the effect of varying the number of fuel injection holes (N = 3, 4, 5, 6) on the FTF and flame dynamics in a model afterburner combustor. Using acoustic excitations, the FTF was measured across a range of frequencies, with flame behavior analyzed via high-speed imaging and chemiluminescence techniques. Results reveal that the FTF gain exhibits dual-peak characteristics, initially decreasing and then increasing with higher N values. The frequencies of these gain peaks shift to higher values as N increases, while the time delay between velocity and heat release rate fluctuations decreases, indicating a faster flame response. Flame morphology analysis shows that higher N leads to shorter, taller flames due to enhanced fuel distribution and mixing. Detailed examination of flame dynamics indicates that different pulsation modes dominate at various frequencies, elucidating the observed FTF behavior. This research provides novel insights into the optimization of fuel injection configurations to enhance combustion stability in afterburners, advancing the development of more reliable and efficient aerospace propulsion systems. Full article

In high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) imaging, the azimuth multi-channel technique effectively suppresses azimuth ambiguity, serving as a reliable approach for achieving wide-swath imaging. However, due to mechanical vibrations of the platform and airflow instabilities, airborne SAR may experience errors in attitude and flight path during operation. Furthermore, errors also exist in the antenna patterns, frequency stability, and phase noise among the azimuth multi-channels. The presence of these errors can cause azimuth multi-channel reconstruction failure, resulting in azimuth ambiguity and significantly degrading the quality of HRWS images. This article presents a novel error correction method for airborne HRWS SAR based on azimuth-variant attitude and range-variant Doppler domain pattern, which simultaneously considers the effects of various errors, including channel attitude errors and Doppler domain antenna pattern errors, on azimuth reconstruction. Attitude errors are the primary cause of azimuth-variant errors between channels. This article uses the vector method and attitude transformation matrix to calculate and compensate for the attitude errors of azimuth multi-channels, and employs the two-dimensional frequency-domain echo interferometry method to calculate the fixed delay errors and fixed phase errors. To better achieve channel error compensation, this scheme also considers the estimation and compensation of Doppler domain antenna pattern errors in wide-swath scenes. Finally, the effectiveness of the proposed scheme is confirmed through simulations and processing of airborne real data. Full article

This paper deals with the design and the robustness analysis of a model predictive control (MPC) for the position tracking of primary flight movables driven by electro-mechanical actuators. This study is, in particular, focused on a rotary electro-mechanical actuator (EMA) by UMBRAGROUP, employing a patented mechanical transmission based on a differential ball-screw mechanism characterized by a huge gear ratio. To obtain a baseline reference, conventional PID regulators were initially optimized by using multi-objective cost functions based on tracking accuracy, load disturbance rejection, and power consumption. The position regulator was then replaced by an MPC regulator, designed to balance performance, computational resources, and safety constraints. A nonlinear physics-based simulation model of the EMA, entirely developed in the Matlab–Simulink environment and validated with experiments, was used to compare the two control strategies. The simulation results in both the time and frequency domains highlight that the MPC solution provides faster and more accurate position tracking, improved dynamic stiffness, and reduced power absorption. Finally, the robustness against model uncertainties of the MPC was addressed by imposing random and combined deviations of model parameters from the nominal values (via Monte Carlo analysis). The results demonstrate that the implementation of MPC control laws could enhance the stability and the reliability of EMAs, thus supporting their application for safety-critical flight control functions. Full article

Loop shaping the controller for high-order systems, especially in the presence of flexible transmission components such as elastic shafts, gearboxes, and belts commonly found in servo systems, poses significant challenges. Therefore, developing a non-parametric, versatile tuning algorithm that adapts to multi-order systems is essential for general control applications. This article first obtains the frequency characteristics of plants through a frequency sweep. Then, based on preset frequency domain specifications, the boundaries representing disturbance rejection and stability constraints are defined in the complex plane with explicit mathematical and graphical expressions. Subsequently, a system of equations is developed based on the tangency between the open-loop curve of the system and the boundaries in the complex plane. On this basis, a versatile tuning algorithm is designed to calculate parameters of a PI controller cascaded with a low-pass filter that ensures the system meets the preset constraints. The proposed approach does not rely on parametric modeling, and the zeros and poles of the controller can be flexibly placed. Experimental validation is carried out on mechanical platforms. Full article

Reliable estimation of operational modal parameters is essential in structural health monitoring (SHM), particularly when these parameters serve as damage-sensitive features. Modern distributed monitoring systems, often employing digital MEMS accelerometers, must account for timing uncertainties across sensor networks. Clock irregularities can lead to non-deterministic sampling, introducing uncertainty in the identification of modal parameters. In this paper, the effects of timing variability throughout the network are propagated to the final modal quantities through a Monte-Carlo-based framework. The modal parameters are identified using the covariance-driven stochastic subspace identification (SSI-COV) algorithm. A finite element model of a steel cantilever beam serves as a test case, with timing irregularities modeled probabilistically to simulate variations in sensing node clock stability. The results demonstrate that clock variability at both intra-node and inter-node levels significantly influences mode shape estimation and introduces systematic biases in the identified natural frequencies and damping ratios. The confidence intervals are calculated, showing increased uncertainty with greater timing irregularity. Furthermore, the study examines how clock variability impacts damage detection, offering metrological insights into the limitations of distributed vibration-based SHM systems. Overall, the findings offer guidance for designing and deploying monitoring systems with independently timed nodes, aiming to enhance their reliability and robustness. Full article

In practical applications, precise tuning of current controllers is essential for achieving desirable dynamic performance and stability margins. Traditional tuning techniques rely heavily on accurate plant parameter identification. However, this process is often challenged by inherent nonlinearities and unmodeled dynamics in motor systems. To address this issue, this paper proposes a current loop parameter tuning algorithm based on open-loop frequency sweeping. As the swept Bode diagram reveals nonlinear factors typically neglected during modeling, it provides a basis for control parameter correction. A pulse-sine voltage injection method is first introduced to identify motor parameters, serving as initial values for the controller. By analyzing the magnitude and phase characteristics of the open-loop transfer function, the delay time constant in the high-frequency range can be accurately identified, and mismatched parameters in the low-to-mid frequency range can be corrected. This method does not rely on complex model structures or extensive online adaptation mechanisms. Experimental results on a mechanical test platform demonstrate that the proposed tuning strategy significantly enhances the current loop’s closed-loop bandwidth and dynamic performance. Full article

This study examines the performance of a GaN HEMT with a 150 nm gate length, fabricated on silicon carbide, across various operational modes, including direct current (DC), radio frequency (RF), and small-signal parameters. The evaluation of DC, RF, and small-signal performance under diverse bias conditions remains a relatively unexplored area of study for this specific technology. The DC characteristics revealed relatively little I_ds at zero gate and drain voltages, and the current grew as V_gs increased. Essential measurements include I_dss at 109 mA and I_dssm at 26 mA, while the peak g_m was 62 mS. Because transconductance is sensitive to variations in V_gs and V_ds, it shows “Vth _roll-off,” where Vth decreases as V_ds increases. The transfer characteristics corroborated this trend, illustrating the impact of drain-induced barrier lowering (DIBL) on threshold voltage (Vth) values, which spanned from −5.06 V to −5.71 V across varying drain-source voltages (V_ds). The equivalent-circuit technique revealed substantial non-linear behaviors in capacitances such as C_gs and C_gd concerning V_gs and V_ds, while also identifying extrinsic factors including parasitic capacitances and resistances. Series resistances (R_gs and R_gd) decreased as V_gs increased, thereby enhancing device conductivity. As V_gs approached neutrality, particularly at elevated V_ds levels, the intrinsic transconductance (g_mo) and time constants (τ_gm, τ_gs, and τ_gd) exhibited enhanced performance. f_t and f_max, which are essential for high-frequency applications, rose with decreasing V_gs and increasing V_ds. When V_gs approached −3 V, the S₂₁ and Y₂₁ readings demonstrated improved signal transmission, with peak S₂₁ values of approximately 11.2 dB. The stability factor (K), which increased with V_ds, highlighted the device’s operational limits. The robust correlation between simulation and experimental data validated the equivalent-circuit model, which is essential for enhancing design and creating RF circuits. Further examination of bias conditions would enhance understanding of the device’s performance. Full article

The voltage source converters convert the DC to AC in order to interface distributed generation units with the utility grid, typically using an LCL filter to smooth the modulated wave. However, the LCL filter can introduce resonance, potentially cause instability, and necessitate the use of damping techniques, such as active damping, which utilizes feedback from the current control loop to suppress resonance. This paper presents a comprehensive performance assessment of four current-feedback-based active damping (AD) techniques—converter current feedback (CCF), CCF with capacitor current feedback (CCFAD), grid current feedback (GCF), and GCF with capacitor current feedback (GCFAD)—under a broad range of realistic grid disturbances and low switching frequency conditions. Unlike prior works that often analyze individual feedback strategies in isolation, this study highlights and compares their dynamic behavior, robustness, and total harmonic distortion (THD) in eight operational scenarios. The results reveal the severe instability of GCF in the absence of damping and the superior inherent damping property of CCF while demonstrating the comparable effectiveness of GCFAD. Moreover, a simplified yet robust design methodology for the LCL filter is proposed, enabling the filter to maintain stability and performance even under significant variations in grid impedance. Additionally, a sensitivity analysis of switching frequency variation is included. The findings offer valuable insights into selecting and implementing robust active damping methods for grid-connected converters operating at constrained switching frequencies. The effectiveness of the proposed methods has been validated through both MATLAB/Simulink simulations and hardware-in-the-loop (HIL) testing. Full article

Background/Objectives: Cows produce antibodies with ultralong CDRH3 segments (ulCABs) that contain a disulfide-stabilized knob domain. This domain is connected to the globular core of the antibody by a β-strand stalk. In the crystal structures, the stalk protrudes from the core in an extended conformation and presents the knob at its distal end. However, the rigidity of this topology has been questioned due to the extensive crystal packing present in most ulCAB crystal structures. To gain more insight into the dynamics of ultralong CDRH3s, we performed a comparative molecular dynamics (MD) study of 19 unique ulCABs. Methods: For all 19 systems, one-microsecond MD simulations were performed in explicit solvent. The analyses included an investigation of the systems’ conformational stability and the dynamics of the knob domain as well as an energetic analysis of the intramolecular knob interactions. Results: The simulations show that the extended stalk–knob conformation observed in the crystal structures is not preserved in solution. There are significant differences in the degree of knob dynamics, the orientations of the knobs, the number of flexible stalk residues, and the frequency of the motions. Furthermore, interactions between the knob and the light chain (LC) of the ulCABs were observed in about half of the systems. Conclusions: The study reveals that pronounced knob dynamics is a general feature of ulCABs rather than an exception. The magnitude of knob motions depends on the system, thus reflecting the high sequence diversity of the CDRH3s in ulCABs. The observed knob–LC interactions might play a role in stabilizing distinct knob orientations. The MD simulations of ulCABs could also help to identify suitable knob fragments as mini-antibodies by suggesting appropriate truncation points based on flexible sites in the stalks. Full article

Algal blooms pose a serious threat not only to the lake ecosystem of Lake Bosten but also by negatively impacting its rapidly developing fisheries and tourism industries. This study focuses on Lake Bosten as the research area and utilizes multi-source remote sensing imagery from Landsat TM/ETM+/OLI and Sentinel-2 MSI. The Adjusted Floating Algae Index (AFAI) was employed to extract algal blooms in Lake Bosten from 2004 to 2023, analyze their spatiotemporal evolution characteristics and driving factors, and construct a Long Short Term Memory (LSTM) network model to predict the spatial distribution of algal-bloom frequency. The stability of the model was assessed through temporal segmentation of historical data combined with temporal cross-validation. The results indicate that (1) during the study period, algal blooms in Lake Bosten were predominantly of low-risk level, with low-risk bloom coverage accounting for over 8% in both 2004 and 2005. The intensity of algal blooms in summer and autumn was significantly higher than in spring. The coverage of medium- and high-risk blooms reached 2.74% in the summer of 2004 and 3.03% in the autumn of 2005, while remaining below 1% in spring. (2) High-frequency algal bloom areas were mainly located in the western and northwestern parts of the lake, and the central region experienced significantly more frequent blooms during 2004–2013 compared to 2014–2023, particularly in spring and summer. (3) The LSTM model achieved an R² of 0.86, indicating relatively stable performance. The prediction results suggest a continued low frequency of algal blooms in the future, reflecting certain achievements in sustainable water-resource management. (4) The interactions among meteorological factors exhibited significant influence on bloom formation, with the q values of temperature and precipitation interactions both exceeding 0.5, making them the most prominent meteorological driving factors. Monitoring of sewage discharge and analysis of agricultural and industrial expansion revealed that human activities have a more direct impact on the water quality of Lake Bosten. In addition, changes in lake area and water environment were mainly influenced by anthropogenic factors, ultimately making human activities the primary driving force behind the spatiotemporal variations of algal blooms. This study improved the timeliness of algal-bloom monitoring through the integration of multi-source remote sensing and successfully predicted the future spatial distribution of bloom frequency, providing a scientific basis and decision-making support for the sustainable management of water resources in Lake Bosten. Full article