Search Results (6,651)

In predictive maintenance frameworks, risk curves are used as interpretable, real-time indicators of equipment degradation. However, existing approaches generally assume a monotonically increasing trend and neglect the corrective effect of maintenance, resulting in unrealistic or overly conservative risk estimations. This paper addresses this limitation by introducing a novel method that dynamically corrects risk curves through a quantitative measure of maintenance effectiveness. The method adjusts the evolution of risk to reflect the actual impact of preventive and corrective interventions, providing a more realistic and traceable representation of asset condition. The approach is validated with case studies on critical feedwater pumps in a combined-cycle power plant. First, individual maintenance actions are analyzed for a single failure mode to assess their direct effectiveness. Second, the cross-mode impact of a corrective intervention is evaluated, revealing both direct and indirect effects. Third, corrected risk curves are compared across two redundant pumps to benchmark maintenance performance, showing similar behavior until 2023, after which one unit accumulated uncontrolled risk while the other remained stable near zero, reflected in their overall performance indicators (0.67 vs. 0.88). These findings demonstrate that maintenance-corrected risk curves enhance diagnostic accuracy, enable benchmarking between comparable assets, and provide a missing piece for the development of realistic, risk-informed predictive maintenance strategies. Full article

Timely detection of leaks is essential for the safe and reliable operation of pressure vessels used in superconducting systems, aerospace, and medical equipment. To address the lack of efficient online leak detection methods for such vessels, this paper proposes a quasi-distributed fiber Bragg grating (FBG) sensing network combined with theoretical stress analysis to diagnose vessel conditions. We analyze the stress–strain distributions of vacuum vessels under varying pressures and examine stress concentration effects induced by small holes; these analyses guided the design and placement of quasi-distributed FBG sensors around the vacuum valve for online leakage monitoring. To improve measurement accuracy, we introduce a vibration correction algorithm that mitigates pump-induced vibration interference. Comparative tests under three leakage scenarios demonstrate that when leakage occurs during vacuum extraction, the proposed system can reliably detect the approximate leak location. The results indicate that combining an FBG sensing network with stress concentration analysis enables initial localization and assessment of leak severity, providing valuable support for the safe operation and rapid maintenance of vacuum pressure vessels. Full article

This paper presents a bistatic 60 GHz frequency-modulated continuous-wave (FMCW) radar system for non-contact heart rate monitoring, utilizing high-gain Fabry–Perot cavity (FPC) antennas at both the transmitter and receiver. Each FPC antenna integrates a partially reflective surface (PRS) and a metallic ground plane to form a resonant cavity. Compared to conventional patch arrays of the same aperture, the FPC antenna improves the antenna gain from 4.1 dBi to 8.1 dBi at the transmitter and from 3.9 dBi to 7.8 dBi at the receiver, resulting in an overall link budget enhancement of approximately 7.9 dB. This dual high-gain configuration theoretically increases the maximum detection range by a factor of 2.48. The proposed radar system was implemented and experimentally validated under indoor conditions using both calibration targets and human participants. Active measurement results confirm that the bistatic radar equipped with FPC antennas extends the reliable heart rate detection distance by approximately 2.27 times compared to a conventional system, closely matching the theoretical prediction. These results confirm the practicality and effectiveness of FPC antennas in extending both the range and reliability of millimeter-wave vital sign detection systems. Full article

With the enlargement of underground parking lots, the risk of massive smoke and toxic gases generated during a fire will be increased, resulting in significant casualties, property damage, and difficulties in firefighting operations. To address these issues, installation of ventilation fans and inducer fans together has been proposed to extract smoke and hazardous gases more efficiently to the outside. However, the disturbance of ventilation caused by simultaneous operation of inducer fans and ventilation fans limits smoke extraction efficiency. In some worst cases, smoke disturbance may even lead to further smoke spread. Therefore, this study aims to suggest an efficient smoke extraction strategy for underground parking lots equipped with ventilation and inducer fans by optimizing the orientation of ventilation fans in the event of vehicle fires. Computational fluid dynamics-based simulation results showed that installing ventilation fan intakes and exhausts perpendicularly (PE, 90° apart) was more effective in controlling smoke than installing them in parallel (PA, horizontally facing each other). In the case of PE, the smoke stagnation area around the intakes decreased markedly from 38.18% to 3.68%. Although the smoke area near the exhausts increased in the PE configuration (53.66%) compared with the PA configuration (26.13%), this indicates that smoke was being effectively transported from the intakes to the exhausts. Furthermore, the overall smoke distribution across the entire space decreased by 4.5% under the PE setup compared with the PA setup. As the intake and exhaust flow rates of the fans increased, the efficiency of smoke removal was enhanced under the PE configuration. Consequently, in environments equipped with both ventilation and inducer fans with given conditions, perpendicular installation of fan intakes and exhausts is more efficient. These results are expected to provide practical design guidelines for ensuring effective smoke extraction in underground parking facilities. Full article

Driving in snowy conditions challenges both human drivers and autonomous systems. Snowfall and ice accumulation impair vehicle control and affect driver perception and performance. Road markings are often obscured, forcing drivers to rely on intuition and memory to stay in their lane, which can lead to encroachment into adjacent lanes or sidewalks. Current lane detectors assist in lane keeping, but their performance is compromised by visual disturbances such as ice reflection, snowflake movement, fog, and snow cover. Furthermore, testing these systems with users on actual snowy roads involves risks to driver safety, equipment integrity, and ethical compliance. This study presents a low-cost virtual reality simulation for evaluating winter lane detection in controlled and safe conditions from a human-in-the-loop perspective. Participants drove in a simulated snowy scenario with and without the detector while quantitative and qualitative variables were monitored. Results showed a 49.9% reduction in unintentional lane departures with the detector and significantly improved user experience, as measured by the UEQ-S (p = 0.023, Cohen’s d = 0.72). Participants also reported higher perceived safety, situational awareness, and confidence. These findings highlight the potential of vision-based lane detection systems adapted to winter environments and demonstrate the value of immersive simulations for user-centered testing of ADASs. Full article

This study investigates the microenvironment under face masks and respirators, focusing on the influence of material and design characteristics on carbon dioxide (CO₂) concentration, temperature, and relative humidity. Masks and respirators were selected from the three main types of personal protective equipment—textile non-medical masks, surgical masks and respirators. Experimental measurements were conducted to assess how geometric parameters (thickness, bulk density), mass (mass per unit area), and structural parameters (air permeability, face cover area) influence the microclimatic conditions during wear. The results show that thickness, mass per unit area, and bulk density have a significant effect on temperature but negligible influence on CO₂ concentration and humidity. In contrast, air permeability and face cover area play a key role in CO₂ and moisture accumulation: higher permeability significantly reduces both, while larger coverage tends to increase them. These findings support the need for an integrated design approach that balances filtration efficiency with respiratory and thermophysiological comfort, contributing to improved protective performance and user acceptance. Full article

Underwater exploration relies heavily on autonomous underwater vehicles and sensor platforms for sustained monitoring of marine environments, yet their operational duration is limited by energy constraints. To enhance energy efficiency, various control strategies have been proposed, including robust, optimal, and disturbance-aware approaches. Recent work introduced a variable structure controller (VSC) with a constant-amplitude control action for depth control of a platform equipped with a variable buoyancy module, achieving an average 22% reduction in energy use in comparison with conventional PID-based controllers. In a separate paper, the conditions for its closed-loop stability were proven. This study extends these works by proposing a controller with a variable-amplitude control action designed to minimize energy consumption. A formal proof of stability is provided to guarantee safe operation even under conservative assumptions. The controller is applied to a previously developed depth-regulated sensor platform using a validated physical model. Additionally, this study analyzes how the controller parameters and mission requirements affect stability regions, offering practical guidelines for parameter tuning. A method to estimate oscillation amplitude during hovering tasks is also introduced. Simulation trials validate the proposed approach, showing energy savings of up to 16% when compared to the controller using a constant-amplitude control action. Full article

The accurate localization of radio frequency (RF) emitters plays a critical role in spectrum monitoring, public safety, and defense applications, particularly in environments where global navigation satellite systems are limited. This study investigates the feasibility of a single unmanned aerial vehicle (UAV) equipped with a Doppler-based software-defined radio sensor to localize modern RF sources without the need for external infrastructure or multiple UAVs. A custom-designed localization system was developed and tested using the L3Harris AN/PRC-152A tactical radio, which represents a class of real-world, dual-use emitters with lower frequency stability than laboratory signal generators. The approach was validated through both emulation studies and extensive field experiments under realistic conditions. The results show that the proposed system can localize RF emitters with an average error below 50 m in 80% of cases even when the transmitter is more than 600 m away. Performance was evaluated across different carrier frequencies and acquisition times, demonstrating the influence of signal parameters on localization accuracy. These findings confirm the practical applicability of Doppler-based single-UAV localization methods and provide a foundation for further development of lightweight, autonomous RF emitter tracking systems for critical infrastructure protection, spectrum analysis, and tactical operations. Full article

This study addresses the challenges encountered in mechanized agricultural fields, particularly the soil disruption associated with conventional horizontal rotary straw cleaning equipment. To mitigate the inefficiency of straw cleaning observed in the current vertical rotary apparatus, this study introduces a vertical rotary fixed-angle straw cleaning device. The essential conditions for establishing the cutter tooth angle were identified through theoretical analysis. Analyzing the kinematics of the cutter tooth to direct the movement of the straw, we determined that the deflection angle of the cutter tooth group (DA) is a critical parameter for enhancing the effectiveness of straw cleaning. A multiphase interaction model encompassing soil, straw, and machinery components was developed utilizing a coupled simulation approach with RecurDyn and EDEM software. The Box–Behnken response surface methodology was employed to systematically investigate the interaction effects of three critical parameters on both the straw cleaning rate and the soil disturbance rate: operation speed (OS), rotation speed of the straw cleaning rotary table (RS), and the DA. For optimization experiments where the OS is set to 2.4 m/s, RS is 400 r/min, and DA is 48°, the straw cleaning rate reaches 94.1% and the soil disturbance rate is 27.2%. This device can efficiently create a localized clean seeding belt for no-till planters without significantly damaging the soil structure, providing an innovative solution for the development of low-disturbance, high-efficiency conservation tillage equipment. Full article

Chronic obstructive pulmonary disease (COPD) is a progressive respiratory condition, contributing significantly to global morbidity and mortality. Traditional diagnostic tools are effective in diagnosing COPD. However, these tools demand specialized equipment and expertise. Advances in artificial intelligence (AI) provide a platform for enhancing COPD diagnosis by leveraging diverse data modalities. The existing reviews primarily focus on single modalities and lack information on interpretability and explainability. Thus, this review intends to synthesize the AI-powered frameworks for COPD identification, focusing on data modalities, methodological innovation, evaluation strategies, and reporting limitations and potential biases. By adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic search was conducted across multiple repositories. From an initial pool of 1978 records, 22 studies were included in this review. The included studies demonstrated exceptional performance in specific settings. Most studies were retrospective and limited in diversity, lacking generalizability and external or prospective validation. This review presents a roadmap for advancing AI-assisted COPD detection. By highlighting the strengths and limitations of existing studies, it supports the development of future research. Future studies can utilize the findings to build models using prospective, multicenter, and multi-ethnic validations, ensuring generalizability and fairness. Full article

The traditional continuous, quantitative spraying technology ignores the severity of pests, diseases and grasses, spatial distribution and other differences, resulting in low effective utilization of pesticides, environmental pollution and other problems. Variable-rate spray technology has become an important development direction in the field of precision agriculture by dynamically sensing crop canopy morphology, pest and disease distribution, and environmental parameters, adjusting the application amount in real time, and significantly improving pesticide utilization. In this study, we systematically review the core progress of variable-rate spray technology; focus on the technical system of information detection, spray volume model, and control system; analyze the current bottlenecks; and propose an optimization path to adapt to the complex agricultural conditions. At the level of information perception, LiDAR, machine vision, and multi-source sensor fusion technology constitute the main perception architecture, and infrared and ultrasonic sensors assist target recognition in complex scenes. In the construction of the spray volume model, models based on canopy volume, leaf area density, etc., are used to realize dynamic application decision by fusing equipment operating parameters, pest and disease levels, meteorological conditions, and so on. The control system takes the solenoid valve + PID control as the core program, and improves the response speed through PWM regulation and closed-loop feedback. The current technical bottlenecks are mainly concentrated in the sensor dynamic detection accuracy, model environmental adaptability, and the reliability of the execution parts. In the future, it is necessary to further promote anti-jamming multi-source heterogeneous sensor data fusion, multi-factor adaptive spray model development, lightweight edge computing deployment, and solenoid valve structural parameter optimization and other technical research, with a view to promoting the application of variable-rate spray technology to the field on a large scale and providing a theoretical reference and technological support for the green transformation of agriculture. Full article

Designing an effective electrical model for charged water bodies is of great significance in reducing the risk of electric shock in water and enhancing the safety and reliability of electrical equipment. Aiming to resolve the problems faced in using existing charged water body modeling methods, a practical circuit model of a charged water body is developed. The basic units of the model are simply constructed using fractional-order resistance–capacitance (RC) parallel circuits. The state variables of the model can be obtained by solving the circuit equations. In addition, a practical method for obtaining the circuit model parameters is also developed. This enables the estimation of the characteristics of charged water bodies under different conditions through model simulation. The effectiveness of the proposed method is verified by comparing the estimated voltage and leakage current of the model with the actual measured values. The comparison results show that the estimated value of the model is close to the actual characteristics of the charged water body. Full article

This paper presents a new coupled fixed-point theorem for a pair of set-valued mappings acting on the Cartesian product of $(m_1, m_2)$- and $(n_1, n_2)$-quasi-metric spaces. Within the general, non-symmetric quasi-metric setting, we establish the existence of an approximate coupled fixed point. Moreover, under the additional assumption of $q_0$-symmetry, we guarantee the existence of a coupled fixed point. Together, these results extend and unify several known theorems in fixed-point theory for quasi-metric and asymmetric spaces. We illustrate the obtained results regarding fixed points when the underlying space is equipped with a graph structure and, thus, sufficient conditions are found to guarantee the existence of a subgraph with a loop with a length greater than or equal to 2. Full article

Conventional ridging and mulching machines struggle to perform effectively in yellow sand substrates due to their loose texture, high collapsibility, and strong fluidity, which compromise ridge stability and operational quality. To address these challenges, this study proposes the development of an integrated rotary tillage, ridging, and film-mulching machine specifically designed to meet the agronomic requirements of tomato cultivation in greenhouse environments with yellow sand substrate. Based on theoretical analysis and parameter calculations, a soil transportation model was established, and the key structural parameters—such as blade arrangement and helical shaft geometry—were determined. A discrete element method (DEM) simulation was employed to construct a contact model for the yellow sand–slag mixed substrate. A combination of single-factor experiments and Box–Behnken response surface methodology was used to investigate the effects of forward speed, shaft rotational speed, and tillage depth on ridge stability and operational performance. The simulation results indicated that a forward speed of 0.82 m·s⁻¹, shaft speed of 260 rpm, and tillage depth of 150 mm yielded the highest ridge stability, with an average of 95.7%. Field trials demonstrated that the ridge top width, base width, height, and spacing were 598.6 mm, 802.3 mm, 202.4 mm, and 1002.8 mm, respectively, with an average ridge stability of 94.3%, differing by only 1.4 percentage points from the simulated results. However, a quantitative traction/energy comparison with conventional equipment was not collected in this study, and we report this as a limitation. The energy consumption is estimated based on power usage and effective field capacity (EFC) under similar operating conditions. Soil firmness reached 152.1 kPa, fully satisfying the agronomic requirements for tomato cultivation. The proposed machine significantly improves operational adaptability and ridge stability in yellow sand substrate conditions, providing robust equipment support for efficient greenhouse farming. Full article

This paper presents a novel gateway-centric architecture for context-aware trust evaluation in Internet of Battle Things (IoBT) environments. The system is structured across multiple layers, from embedded sensing devices equipped with internal modules for signal filtering, anomaly detection, and encryption, to high-level data processing in a secure cloud infrastructure. At its core, the gateway evaluates the trustworthiness of sensor nodes by computing reputation scores based on behavioral and contextual metrics. This design offers operational advantages, including reduced latency, autonomous decision-making in the absence of central command, and real-time responses in mission-critical scenarios. Our system integrates supervised learning, specifically Decision Tree Regression (DTR), to estimate reputation scores using features such as transmission success rate, packet loss, latency, battery level, and peer feedback. The results demonstrate that the proposed approach ensures secure, resilient, and scalable trust management in distributed battlefield networks, enabling informed and reliable decision-making under harsh and dynamic conditions. Full article