Search Results (173)

Vision-sensor-based intelligent perception systems are increasingly used in safety-critical scenarios such as autonomous driving, edge surveillance, and Internet-of-Things (IoT) platforms. The vulnerability of deep neural networks to adversarial examples raises security concerns for sensor-acquired visual data in such systems, motivating the study of output-probability-based adversarial example detection methods under controlled benchmark settings. Existing input-level sensitivity detection methods generally rely on static perturbation scales or single-state metrics. When confronted with heterogeneous attacks, such as one-step attacks and iterative attacks, as well as complex tasks with high class density, these methods often suffer from unstable metric directions and insufficient boundary probing capability. To address these issues, this paper proposes a dual-domain adaptive adversarial example detection method based on Multi-scale Input Sensitivity (MSIS). The proposed method introduces a Manifold-Motivated Micro-scale Probing (MMP) mechanism and a Dual-State Sensitivity Fusion (DSF) mechanism. MMP adopts a task-level perturbation scaling strategy motivated by the compressed inter-class manifold structures observed in high-density classification tasks, thereby alleviating perturbation overflow and improving boundary probing effectiveness. DSF employs temperature scaling to extract sensitivity features under both the native state and the smoothed state, and alleviates the directional conflict of heterogeneous attacks under a single metric through dual-state joint modeling. Experimental results demonstrate that, without modifying the parameters of the target model, the proposed method achieves favorable detection performance against representative attacks, including FGSM, PGD, and C&W, on the CIFAR-10 and CIFAR-100 datasets. Taking the CIFAR-10 + ResNet-18 configuration as an example, the detection AUC of the proposed method against the PGD attack reaches 97.75%, an improvement of 24.32 percentage points over the best-performing non-intrusive baseline method, Energy Score (73.43%), with the lowest FPR@95TPR dropping to 7.75%. Under the CIFAR-10 + ResNet-50 configuration, the detection AUC against the PGD attack further reaches 99.14%. Meanwhile, even when compared with PASA (2024), the latest intrusive method requiring access to model gradients, the average AUC of the proposed method on CIFAR-10 + ResNet-18 (97.49%) is still 18.81 percentage points higher, and its inference latency is only 1/11th that of PASA. These results suggest that introducing task-level spatial-domain scaling and temperature-state adaptation can improve output-probability-based adversarial example detection under non-intrusive benchmark settings, providing algorithmic evidence for output-probability-based detection of adversarial perturbations in visual classification tasks. Full article

Variations in wind-turbine rotor speed and converter power margin under different operating conditions constrain the frequency-support power output of wind turbines, thereby affecting the controllability and stability of the frequency-support response. To address this problem, this paper proposes a dual virtual synchronous generator (VSG) coordinated control method for energy-storage doubly fed induction generator wind turbines based on frequency-support power-response equivalence. First, frequency-support power-response models are established for the VSGs implemented at the rotor-side converter and the grid-side converter to describe the active-power dynamic characteristics of the two frequency-support channels. Second, using the target inertial-support power response as the reference, the dual-VSG parameter configuration is transformed into a power-response consistency optimization problem. Furthermore, considering rotor speed, state of charge (SOC), and the grid-side converter upward power margin, the inertia-support and primary frequency regulation power contributions are assigned between the stator and grid-side converter channels. Hardware-in-the-loop validation results show that the proposed method coordinates the dual-channel frequency-support power output under four typical operating conditions with high/low wind speeds and high/low SOC levels, maintains a consistent frequency-support power response, and achieves controllable and stable frequency support over a wide operating range. Full article

Rotational energy harvesters are often constrained by narrow operating bandwidths and sensitivity to specific rotational regimes, limiting their effectiveness under variable-speed conditions. This work presents an orientation-adaptive dual-mode piezoelectric rotational energy harvester capable of broadband energy extraction across diverse rotational and vibration environments. The proposed design combines gravity-induced magnetic excitation at low rotational speeds with centripetal-force-induced nonlinear dynamics at higher rotational speeds, enabling passive transition between operating modes without active tuning. A coupled nonlinear electromechanical model is developed to investigate the interactions among gravitational forcing, magnetic coupling, centripetal loading and piezoelectric transduction. Numerical simulations reveal the transition from gravity-dominated mono-stable behaviour to broadband nonlinear operation as rotational speed increases. Experimental validation is conducted using representative vibration profiles from aerospace, automotive, civil infrastructure and industrial environments. The results demonstrate clear orientation-dependent performance, with the downward cantilever configuration achieving a maximum average power output of 57.8 μW under aerospace elevation excitation, whilst the upward configuration exhibits improved robustness under broadband random vibrations. The proposed orientation-adaptive framework provides a compact, stator-independent solution for broadband rotational energy harvesting under realistic operating conditions. Full article

This paper investigates the problem of multi-target search by an Autonomous Underwater Vehicle (AUV) swarm in unknown three-dimensional (3D) underwater environments with obstacles under limited communication conditions. To address this problem, a distributed cooperative search framework is proposed. Within this framework, an adaptive dual-state search mechanism driven by a target response function is designed. This mechanism enables the swarm to transition between independent large-scale roaming search and precise cooperative search. On this basis, a multi-target search method is developed by integrating a virtual force model, motion-constrained 3D Particle Swarm Optimization (PSO), and a sectional 3D tangent-plane obstacle-avoidance method. Simulation results demonstrate the effectiveness and engineering feasibility of the proposed framework. Under the conditions of unknown terrains and communication limits, the AUV swarm can adaptively execute state transitions, safely avoid 3D obstacles, and complete multi-target search tasks. Specifically, as the swarm size increases from 30 to 60 AUVs, the mean number of iterations drops from 432.97 to 269.73, while the total energy consumption expectedly rises from 11.79 × 10⁴ to 15.51 × 10⁴, reflecting a well-balanced trade-off between efficiency and cost. This study provides a practical distributed control reference for AUV swarms in complex communication-constrained underwater scenarios. Full article

Plant immune genes are traditionally classified as resistance genes, susceptibility genes, or positive/negative regulators of defense. However, this framework does not fully explain a subset of immune-associated genes that display paradoxical disease phenotypes, in which genetic disruption enhances resistance despite the normal involvement of these genes in defense-related processes. GSL5/PMR4 is a representative example. As a pathogen-induced callose synthase, GSL5 contributes to papillary callose deposition and structural defense. Paradoxically, loss of GSL5 confers resistance to powdery mildew through salicylic acid- and N-hydroxypipecolic acid-associated pathways, as well as broad-spectrum resistance to Plasmodiophora brassicae through jasmonic acid-dependent immunity. Here, we refer to such genes as dual-state immune regulators, whose functional presence and genetic disruption promote resistance through distinct immune states. Similar regulatory patterns have been reported in several immune-related processes, including MAPK signaling, calcium influx, membrane trafficking, and receptor-proximal immune signaling. Representative examples include the MEKK1–MKK1/MKK2–MPK4 module, CNGC2/CNGC4, EXO70B1 and BIK1. This review uses GSL5 as a central example to discuss paradoxical immune phenotypes and dual-state immune regulators in plants, focusing on their biological features, potential mechanisms, and implications for resistance breeding. Full article

High-speed permanent magnet synchronous motors (PMSMs) used in electric pump-fed liquid rocket engines require stator shielding sleeves to prevent corrosive propellants from causing harm under cyclic pressure. However, metallic sleeves suffer significant losses due to eddy currents. Conversely, pure carbon fiber reinforced polymer (CFRP) sleeves have failed when exposed to 98% H₂O₂. Micro-CT analysis of a failed pump sleeve reveals a four-stage failure mechanism. Manufacturing defects caused matrix cracking, which propagated under pressure and thermal cycling. This progression resulted in the formation of through-thickness leakage paths, which ultimately triggered catalytic decomposition and explosion. To address these issues, an improved dual-layer sleeve is proposed, featuring a 2.5 mm PEEK 450G liner and a 2.0 mm T700S/epoxy CFRP overwrap. Finite Element Analysis (FEA) indicates peak von-Mises stresses of 86.25 MPa and 112.16 MPa, yielding Tsai–Wu safety factors of 2.9 and 1.7. Furthermore, various tests, including immersion, fatigue, burst, hydraulic, and thermal evaluations, demonstrate a burst margin of 2.37× at 7.12 MPa, with only 0.19% increase in mass. This design effectively eliminates leakage pathways while preserving zero eddy-current loss and ensuring a low weight. Full article

Direct Torque Control (DTC) for induction motors (IMs) is an advanced method derived from Field-Oriented Control (FOC). In DTC, a voltage source inverter (VSI) is employed to directly regulate the stator flux linkage and electromagnetic torque through space vector modulation (VSM), where the optimal switching vector is selected for the VSI. Similarly to FOC, the stator flux and electromagnetic torque are independently controlled to deliver enhanced dynamic performance. However, DTC still suffers from certain drawbacks, such as slow transient response, limited dynamic performance, and high ripples in torque and flux. In this paper, an improved DTC method is proposed for a three-phase squirrel-cage induction motor. Specifically, a Type-2 fuzzy logic controller is employed to regulate both the stator flux and electromagnetic torque (T2FLC). The proposed method (FLCDTC) combines a three-level VSI with dual-band hysteresis (DBHW) switching to generate the gating signals for the insulated gate bipolar transistors (IGBTs). This approach effectively reduces the total harmonic distortion (THD) in torque and stator current, lowers the common-mode voltage (CMV), and enhances the overall motor performance. Simulation results under random noise distribution demonstrate the robustness of the proposed controller, even at low operating speeds. Finally, the effectiveness of the algorithm is validated in real-time through hardware-in-the-loop (HIL) implementation. Full article

Human performance in critical environments is frequently degraded by mistimed communication delivered during periods of visual–cognitive saturation. In such settings, failures arise not only from individual limitations but also from poor coordination between operators under rapidly changing workload conditions. We present a dual-loop neuro-adaptive simulation framework based on real-time spectral–topographic EEG representations, in which multichannel cortical activity is transformed into dynamic spatial maps and decoded to regulate both operator assistance and team communication. The system integrates 14-channel wireless EEG (Emotiv EPOC X, 256 Hz), gaze tracking, telemetry, and communication events through an LSL-based multimodal synchronization pipeline. A hybrid CNN–LSTM model processes sequences of spectral-topographic EEG maps to classify three operationally actionable neurocognitive states—Channelized Attention, Diverted Attention, and Surprise/Startle—while also estimating a continuous Cognitive Load Index (CLI). These representation-derived features are then used by a multi-agent proximal policy optimization (MAPPO) controller to generate two coordinated outputs: (i) adaptive haptic guidance for the pilot, designed to reduce reliance on overloaded visual and auditory channels, and (ii) a traffic-light communication gate for the telemetry engineer, regulating whether radio intervention should proceed, be delayed, or be withheld. In a high-fidelity dual-station simulation with 25 pilot–engineer pairs, the proposed framework was associated with a reduction of more than 30% in communication breakdown errors relative to open-loop telemetry, with the strongest effects observed during peak-load windows, while preserving realistic task progression. It also improved pilot reaction time to time-critical warnings and reduced engineer decision load under the tested conditions. These findings support the use of spectral-topographic EEG representations as a practical basis for combining multimodal neurophysiological sensing, spatiotemporal pattern decoding, and adaptive coordination in high-pressure human–machine teams. At the same time, the study should be interpreted as evidence of controlled feasibility in a simulated setting rather than as definitive proof of field-level generalization. We further discuss deployment constraints and propose privacy-by-design safeguards to ensure that neurocognitive signals are used exclusively for operational adaptation rather than employability assessment or performance scoring. Full article

The dual-inverter open-winding permanent magnet synchronous motor (OW-PMSM) drive system exhibits significant advantages for electric vehicles with dual energy sources, particularly in achieving coordinated energy management and efficient power allocation between the sources. Based on the dual-inverter OW-PMSM drive configuration, this paper proposes two stator current planning algorithms: one aims to minimize the electrical losses during motor operation and the other aims to maximize the power allocation range of the dual inverters, respectively. Building upon this, a geometric algorithm for stator voltage vector allocation is proposed to achieve smooth switching of the motor between the two algorithms. This enhances the tracking performance of the electromagnetic torque and d-axis current during motor operation, while ensuring that the motor operates within its steady-state range, thereby improving system stability. Finally, simulations and experiments are conducted on the proposed algorithm to verify its feasibility and advantages. Full article

This paper deals with the investigation of the best topology of a five-phase fault-tolerant spoke-type permanent magnet (PM) motor for the propulsion of a multirotor aerial vehicle. This study is carried out through four stages. First, an assessment of the PM configuration effect on motor performance, considering three positions, namely surface PM, spoke-type PM, and V-shape PM. Second, an evaluation of the optimisation formulation problem on motor performance, where three formulations, respectively, involving either electric motor (EM) efficiency, EM efficiency and torque, or EM efficiency and active weight are considered for this purpose. Third, the stator winding configuration effect on performance in healthy and faulty operation mode (OM), e.g., open-circuit fault (OC) and inter-turn short-circuit (ITSC) fault, is also assessed. This evaluation is performed considering two winding configurations, namely fractional slot concentrated winding (FSCW) with single-layer (SL) or dual-layer (DL) winding. Fourth, a modified rotor geometry is proposed, based on the airgap length variation, in order to increase the airgap flux density amplitude and thus improve the motor torque and power densities. A comparative study, in this case, is performed with a classical rotor geometry in order to assess their influence on motor performance in healthy and faulty operation mode (OM). In addition, this paper presents a quantitative comparison of the proposed five-phase motor and a three-phase spoke-type PM motor, where the results, in healthy and faulty OM, show the interest of the proposed multiphase motor. Full article

To elucidate the damping mechanism of platform dry friction dampers for turbine blades and optimize their design parameters, this study establishes a two-dimensional global–local unified sliding dry friction damping model. This model comprehensively accounts for the blade’s bending-torsion coupling vibration characteristics and the dual-state behavior of the damper, encompassing both stick and slip phases. An iterative solution strategy combining finite element methods with in-house developed programs is employed to simulate the vibration response of turbine blades equipped with dampers under multiple loading conditions. The influence of normal pressure and dimensionless normal pressure on the blade’s vibration characteristics, equivalent stiffness, and equivalent damping is systematically analyzed. To validate the reliability of the simulation results, a dedicated test platform capable of independently simulating centrifugal force effects was constructed, and modal tests as well as vibration response tests were conducted. The results demonstrate that the proposed model accurately describes the nonlinear energy dissipation behavior of dry friction damping, providing a reliable theoretical basis for blade vibration response analysis. Dimensionless normal pressure is identified as a key parameter influencing vibration reduction effectiveness. The resonant amplitude of the blade exhibits a non-monotonic trend, initially decreasing and then increasing with rising dimensionless normal pressure. The optimal dimensionless normal pressure range is found to be 20–30, within which the blade vibration amplitude can be reduced by more than 50%. Experimental verification confirms that the vibration reduction and energy dissipation mechanism of the damping block aligns closely with simulation results, achieving a maximum vibration reduction of 72.6%. Moreover, the optimal dimensionless normal pressure values correspond well with simulation predictions. Based on the optimal dimensionless normal pressure, a forward design method for platform dampers is proposed, which can provide theoretical support and engineering guidance for the optimal design of vibration reduction structures in aero-engine turbine blades. Full article

With the increasing penetration of wind and solar renewable energy into modern power systems, grids exhibit ‘dual-high’ (i.e., a high proportion of both renewable energy and power electronic devices) and ‘dual-low’ (i.e., low equivalent rotational inertia and low short-circuit capacity) structural characteristics. This leads to critical challenges, notably insufficient short-circuit capacity, declining voltage and frequency stability, and weakened system damping. To address the stability requirements of new power systems, this study proposes and systematically investigates a variable-speed synchronous condenser based on AC excitation technology. The research encompasses the operational principles, starting mechanisms, and control strategies of the device, with a particular focus on analyzing its stator-flux-oriented vector control method and active–reactive power decoupling regulation mechanism. By independently adjusting the frequency, amplitude, and phase of the AC excitation on the rotor side, the system achieves a millisecond-level dynamic reactive power response, rapid frequency support, and self-starting capability without the need for external starting devices. To validate the effectiveness of the theoretical analysis and engineering practicality, this study presents grid-connected operational tests using a 3600 kVar engineering prototype at a wind farm. The test results demonstrate that the variable-speed synchronous condenser performs excellently in speed regulation, dynamic reactive power response, and primary frequency modulation. It effectively provides short-circuit capacity, enhances system damping, and significantly improves the voltage and frequency stability of power grids with high penetration of renewable energy. This study offers innovative technical pathways and empirical evidence for constructing a stability support system that meets the developmental needs of new power systems. It holds significant theoretical value and engineering guidance for promoting the smooth transition of power grids from synchronous machine-dominated to power electronics-based architectures. Full article

Traditional stator-permanent magnet flux-reversal motors have the problems of large cogging torque, limited improvement of power density, and low fault-tolerant performance. Based on the traditional flux-reversal motor, this paper proposes a design scheme of a flux-reversal motor with a stator-segmented double-winding and double-sequence permanent magnet structure. The motor adopts a stator-segmented modular design, each independent stator segment is connected by permanent magnets, and a bipolar permanent magnet array is arranged on the teeth of the stator segment. Meanwhile, a double-winding system composed of independent power windings and fault-tolerant windings is configured to realize the dual characteristics of high power density and high reliability. A two-dimensional finite element model is established to simulate and analyze the motor, which verifies the feasibility of the motor structure design. The simulation results show that the motor has improved operation stability, better fault-tolerant performance, and theoretically lower maintenance cost, as well as being especially suitable for the petroleum and chemical industries, electric vehicles, aerospace, and other application fields with high requirements for motor reliability and power density. Full article

Rotatory electric motors provide low efficiency in the case of linear motion. The reason for this is the mechanical conversion system required to convert rotary torque to linear thrust force. In this paper, two novel linear machines i.e., a Dual-Mover Segmented Secondary Hybrid Excited Linear Flux Switching Machine (DMSSHELFSM) and Dual-Stator Segmented Secondary Hybrid Excited Linear Flux Switching Machine (DSSSHELFSM), were investigated and compared for a ropeless vertical elevator system. The novelties of these designs include both series and parallel magnetic circuits, a complementary AC coil structure, and their unequal primary tooth width. Results reveal that the DSSSHELFSM exhibits better performance with higher and more sinusoidal flux linkage, higher thrust force, and a robust mechanical structure. Secondly, the selected linear motor was optimized using a deterministic optimization approach. An average thrust force of 10kN and a thrust force ripple ratio of less than 10% were considered as performance constraints during the optimization process. Finally, full-scale no-load experimental results were obtained, and they validated the research. Full article

Existing model predictive control (MPC) schemes based on virtual voltage vectors (VVVs) for dual three-phase permanent magnet synchronous motors (DT-PMSMs) typically employ a limited set of voltage vectors, which restricts further improvement in steady-state performance. Moreover, the design of switching sequences lacks systematic consideration, focusing mainly on harmonic current suppression while neglecting practical engineering challenges associated with software-layer implementation. This paper proposes an optimized model predictive torque control (MPTC) method for DT-PMSMs using an expanded voltage vector set. First, to enhance steady-state performance, an extended control set of voltage vectors is designed, which introduces not only new directions but also two distinct voltage amplitude levels, resulting in a total of 48 voltage vectors. Second, to alleviate the significant computational burden caused by traversing the extended set for prediction, a candidate voltage vector selection table is constructed based on the sector position of the stator flux linkage and the requirements for torque and flux adjustment. This approach reduces the computational load to only 10 predictive calculations per control cycle, avoiding exhaustive traversal of the extended set. Furthermore, for all VVVs in the control set, a switching sequence combining active voltage vectors with zero vectors is designed to facilitate straightforward digital implementation. Finally, experimental results are provided to validate the effectiveness of the proposed method. Full article