Search Results (269)

Aiming at the significant challenges faced by active power filters (APFs) in suppressing low-order harmonic currents (such as second and fourth), this paper proposes a rarefaction suppression method based on quasi-proportional resonance (QPR) control. Firstly, the harmonic mathematical model of APFs in a synchronous, rotating coordinate system is established to reveal the inherent defects of traditional proportional–integral (PI) control in low-order harmonic suppression. Theoretical analysis shows that although the proportional resonant (PR) controller can achieve zero-steady-state-error tracking of specific frequency harmonics, its narrow bandwidth and low robustness may easily lead to system oscillation. Therefore, the QPR control strategy is introduced. By superimposing a low-pass filter with an adjustable cut-off frequency on the resonant link, the bandwidth is significantly broadened and the anti-frequency disturbance ability of the system is enhanced. In addition, the stability of QPR control parameters is analyzed. Finally, the verification based on the experimental platform demonstrates that the proposed method reduces the total harmonic distortion (THD) of the 380 V bus current from 82.18% to 3.45%, and the low-order harmonic current suppression performance is significantly better than the traditional scheme. This research provides an effective solution for the synergistic suppression of low-order harmonic currents. Full article

High-precision speed measurement at low speeds in PMSM drives is hindered by encoder quantization noise. This paper proposes an enhanced extended state observer (ESO)-based method to overcome limitations of conventional approaches such as direct differentiation with the low-pass filter (high noise), the phase-locked loop (PLL)-based method (limited dynamic response), and standard ESO (sensitivity to disturbance). The improved ESO incorporates reference torque feedforward and disturbance feedback, significantly suppressing noise and enhancing robustness. Simulations and experiments demonstrate that the proposed method reduces steady-state speed fluctuation by up to 42% compared to standard ESO and over 90.1% relative to differentiation-based methods, while also improving transient performance. It exhibits superior accuracy and stability across various low-speed conditions, offering a practical solution for high-performance servo applications. Full article

Traditionally used to combat infections, systemic effects of antibiotics are increasingly recognized in the context of absorption through unconventional routes. One such as the ocular surface. This review tackles the bidirectional liver–eye axis, highlighting how trace antibiotic residues from environmental and therapeutic sources affect the tear film, disturb ocular microbiota, and impact liver metabolism. It engages in anatomical pathways, microbial regulation, pharmacokinetics, and systemic immune responses. Additionally, this review discusses forensic uses and new therapeutic strategies, stressing the importance of integrated environmental monitoring and precision medicine to tackle nonmedicinal antibiotic exposure. Due to the absence of results from a systematic literature review, a narrative literature review was undertaken instead. More than 100 studies discussing mechanistic, clinical, and experimental insights were reviewed, with 98 of those studies being documented as source literature. The findings demonstrate that antibiotics may penetrate and be absorbed through the ocular surface, cause modifications of the hepatic first-pass metabolism, and change the activity of cytochrome P450. Correlations were documented between the various liver function biomarkers and the ocular tear film, as well as the thickness of the retinal pigment epithelium. The dysbiosis of eye microbiota may be an indicator of systemic inflammation associated with immune dysregulation. Restoring microbial homeostasis and addressing systemic dysregulation are novel therapeutic approaches, including the use of probiotics, nanoparticle scavengers, and CRISPR. The eye is a sensory organ and a metabolically active organ. Systemically, the eye can affect the liver through the ocular surface and the antibiotics through the liver–eye axis. To protect the systemic health of the individual and the lensed metabolically active eye, the eye and liver must be viewed as a sentinel of systemic balance. Novel therapies will be necessary with the added need for environmental monitoring. Full article

Wire Arc Additive Manufacturing (WAAM) offers high deposition rates and cost-effective production of large metal components but suffers from poor surface quality, particularly surface waviness, which increases post-processing requirements and limits industrial adoption. Since waviness directly impacts structural integrity, resource efficiency, and industrial applicability, understanding how process parameters govern this feature is critical for reducing post-processing requirement. This study systematically investigated the influence of voltage, travel speed, and wire feed speed on surface waviness in aluminum alloy walls fabricated by WAAM. A two-level factorial design with 16 experiments was conducted, and surface waviness was quantified using height gauge measurements relative to the expected bead height. Statistical analyses, including ANOVA and multiple linear regression, were applied to evaluate parameter significance. The results revealed that wire feed speed was the most influential parameter, showing a strong positive correlation with waviness due to excess material deposition. Voltage exhibited a weaker, stabilizing effect, with higher values marginally reducing waviness through improved arc stability, while travel speed had negligible influence within the studied range. The regression model achieved an $R^2$ 0.389, with validation tests indicating reasonable predictive accuracy. These findings demonstrate that controlling wire feed speed is critical for minimizing waviness, while higher voltage may serve as a secondary stabilizing factor. The study was limited to surface waviness; however, future work should consider the role of thermal accumulation, inter-pass temperature, and external disturbances on surface stability. Such insights could enable adaptive parameter control strategies to further reduce post-processing needs and enhance the industrial viability of WAAM. Full article

The solar terminator, due to its unique characteristics, is a remarkable source of atmospheric disturbances. Due to its regularity and constancy, dependent solely on geometric factors, it can serve as a test source of disturbances, which can be used to test the response of the medium through which it passes and determine its state. However, our knowledge of the atmospheric phenomena generated by the terminator is far from complete. One clear indication of the terminator’s influence is geomagnetic disturbances manifested in the vertical and eastward components of the magnetic field measured at magnetic observatories. To determine the sources of geomagnetic disturbances from the solar terminator, which can be identified by the strict phase correlation of these disturbances with the moments of terminator passage, ionospheric irregularities arising during terminator passage were studied. Ionospheric irregularities extending along the boundary of the morning solar terminator were detected in total electron content data, based on measurements by GNSS receivers. Assumptions are made about the possible parameters of the ionospheric current structure that creates variations in the magnetic field associated with the passage of the solar terminator. Full article

This paper presents the development and characterization of a reference high-voltage sensing chain for the calibration and conformity assessment of instrument transformers with Class 0.1-WB3, in the extended frequency range up to 150 kHz, according to IEC 61869. The sensing chain, composed of a high-voltage divider, precision attenuators and high-pass filters, has been specifically developed and characterized. The chain features two parallel measurement paths: the first path, comprising the high-voltage divider and attenuator, is optimized for measuring the fundamental frequency superimposed with high-amplitude harmonics; the second path, consisting of the high-voltage divider followed by a high-pass filter, is dedicated to measuring very-low-level superimposed harmonic components by enhancing the signal-to-noise ratio. These two paths are integrated with a digitizer to form a complete and modular measurement chain. The expanded uncertainty of measurement has been thoroughly evaluated and confirms the chain’s ability to support assessment of instrument transformers with Class 0.1-WB3 compliance. Additionally, the chain architecture enables a future extension up to 500 kHz, addressing the growing need to evaluate instrument transformers under high-frequency power quality disturbances and improving the sensing capability in this field. Full article

Tillage practices can significantly impact soil structure and pore size distribution and connectivity, consequently affecting the shape of the soil water retention curve (SWRC) and its related estimated hydraulic parameters in the top layer of soil. This study investigated the effect of no-tillage (NT) and conventional tillage (CT) practices on SWRCs and their soil hydraulic parameters, estimated by the Brooks–Corey (BC) function at 0–15 and 15–30 cm depths within sugarbeet and corn planting rows in clay loam and sandy loam soils, respectively. Soil water retention curves were measured using the evaporative method (HYPROP). Measured SWRC results were modeled for both untilled and tilled soils using the BC function for each depth in both soils. In clay loam, results indicated that all soil parameters of the BC function, water contents at 330 (θ₃₃₀) and 15,000 (θ_15,000) hPa, and plant available soil water content (AW) were not significantly affected by the type of tillage at either soil depth. The lack of difference in results between NT and CT may be due to considerable soil disturbance, primarily by the harvest process of sugarbeet roots. However, in sandy loam, results indicated that differences occurred in SWRC’s estimated parameters between the NT and CT practices. Averaged across 4 years and two soil depths, the pore size distribution index (λ) and saturated water content (θ_s) were significantly larger under CT than under NT due to greater soil loosening and disturbance caused by multiple passes of the CT process, thereby developing more soil macroporosity. However, the θ₃₃₀ and AW were significantly larger in NT than in CT due to reduced soil disturbance and improved soil structure under NT compared to CT practices. Regardless of tillage, measurements of SWRC are important for determining better irrigation management practices, enabling producers to optimize crop productivity, while saving water and sustaining water quality. Full article

Emergency braking detection plays a vital role in enhancing road safety by identifying potentially hazardous driving behaviors. While existing methods rely heavily on artificial intelligence and computationally intensive algorithms, this paper proposes a lightweight, real-time algorithm for distinguishing emergency braking from non-emergency events using accelerometer and gyroscope signals. The proposed approach applies magnitude calculations and a moving average filters algorithm to preprocess inertial data collected from a six-axis IMU sensor. By analyzing peak values of acceleration and angular velocity, the algorithm successfully separates emergency braking from other events such as regular braking, passing over speed bumps, or traversing damaged roads. The results demonstrate that emergency braking exhibits a unique short-pulse pattern in acceleration and low angular velocity, distinguishing it from other high-oscillation disturbances. Furthermore, varying the window length of the moving average impacts classification accuracy and computational cost. The proposed method avoids the complexity of neural networks while retaining high detection accuracy, making it suitable for embedded and real-time vehicular systems, such as early warning applications for fleet management. Full article

Agricultural drainage canals provide critical habitats for fish species that are highly sensitive to agricultural practices. However, conventional monitoring methods such as capture surveys are invasive and labor-intensive, which means they can disturb fish populations and hinder long-term ecological assessment. Therefore, there is a strong need for effective and non-invasive monitoring techniques. In this study, we developed a practical method using the YOLOv8n deep learning model to automatically detect and quantify fish occurrence in underwater images from a canal in Ibaraki Prefecture, Japan. The model showed high performance in validation (F1-score = 91.6%, Precision = 95.1%, Recall = 88.4%) but exhibited reduced performance under real field conditions (F1-score = 61.6%) due to turbidity, variable lighting, and sediment resuspension. By correcting for detection errors, we estimated that approximately 7300 individuals of Pseudorasbora parva and 80 individuals of Cyprinus carpio passed through the observation site during a seven-hour monitoring period. These findings demonstrate the feasibility of deep learning-based monitoring to capture temporal patterns of fish occurrence in agricultural drainage canals. This approach provides a promising tool for sustainable aquatic ecosystem management in agricultural landscapes and emphasizes the need for further improvements in recall under turbid and low-visibility conditions. Full article

Nano- and microplastics (NMPs), with nanoplastics posing higher risks due to their smaller size and greater capacity for cellular and subcellular penetration, are being referred to as ubiquitous environmental neurotoxicants, due to their ability to pass through biological barriers, including the blood–brain barrier (BBB) and nasal olfactory epithelium, and to remain lodged in neural tissue. Upon uptake, such particles disturb neuronal homeostasis by multiple converging pathways, including oxidative stress, mitochondrial dysfunction, pathological protein aggregation, and chronic neuroinflammation, all closely involved with the molecular signatures of neurodegenerative disorders (Alzheimer’s, Parkinson’s, Amyotrophic Lateral Sclerosis—ALS). In addition to their neurotoxicity, recent findings suggest that NMPs could disturb synaptic communication and neuroplasticity, thereby compromising the brain’s capacity to recover from an injury, a trauma, or neurodegeneration, thus impacting the progression of the disease, our ability to treat it and eventually the efficacy of rehabilitation approaches. Despite these findings, our understanding remains hampered by analytical issues, the scarcity of standard detection methods, and a total lack of longitudinal studies in humans. This review combines multidisciplinary evidence on brain–plastic interactions and calls for accelerated advances in our ability to monitor bioaccumulation in humans, and to integrate neurotoxicology paradigms in the assessment of this underappreciated but growing threat to brain health. 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

This paper presents a structured and experimentally validated approach to the parameter identification, modeling, and real-time speed control of a brushless DC (BLDC) motor. Electrical parameters, including resistance and inductance, were measured through DC and AC testing under controlled conditions, respectively, while mechanical and electromagnetic parameters such as the back electromotive force (EMF) constant and rotor inertia were determined experimentally using an AVL dynamometer. The back EMF was obtained by operating the motor as a generator under varying speeds, and inertia was identified using a deceleration method based on the relationship between angular acceleration and torque. The identified parameters were used to construct a transfer function model of the motor, which was implemented in MATLAB/Simulink R2024b and validated against real-time experimental data using sinusoidal and exponential input signals. The comparison between simulated and measured speed responses showed strong agreement, confirming the accuracy of the model. A proportional–integral (PI) controller was developed and implemented for speed regulation, using a low-cost National Instruments (NI) USB-6009 data acquisition (DAQ) and a Kelly controller. A first-order low-pass filter was integrated into the control loop to suppress high-frequency disturbances and improve transient performance. Experimental tests using a stepwise reference speed profile demonstrated accurate tracking, minimal overshoot, and robust operation. Although the modeling and control techniques applied are well known, the novelty of this work lies in its integration of experimental parameter identification, real-time validation, and practical hardware implementation within a unified and replicable framework. This approach provides a solid foundation for further studies involving more advanced or adaptive control strategies for BLDC motors. Full article

The control of following motion under mesoscale gap flow fields has important applications. The flexible characteristics of the plant, wideband time-varying disturbances caused by the flow field, and requirements of high precision and low overshoot make achieving submicron level accuracy a significant challenge for traditional control methods. This study adopts the control concept of Disturbance Observer Control (DOBC) and uses H_∞ mixed-sensitivity shaping technology to design a Q-filter. Simultaneously, multiple control techniques, such as high-order reference trajectory planning, Proportional-Integral-Derivative (PID) control, low-pass filtering, notch filtering, lead lag correction, and disturbance rejection filtering, are applied to obtain a control system with a high open-loop gain, sufficient phase margin, and stable closed-loop system. Compared to traditional control methods, the new method can increase the open-loop gain by 15 times and the open-loop bandwidth by 8%. We even observed a 150-time increase of the open-loop gain at the peak frequency. Ultimately, the method achieves submicron level accuracy, making important advances in solving the control problem of semiconductor equipment. Full article

Aiming at the problem that the aggravation of the wheel tread wear of high-speed trains leads to the deterioration of train operation performance and an increase in re-profiling times, a multi-objective data-driven optimization design method for the wheel profile is proposed. Firstly, the chaotic map is introduced into the population initialization process of the golden jackal algorithm. In the later stage of the algorithm iteration, random disturbance is introduced with optimization algebra as the switching condition to obtain an improved optimization algorithm, and the performance index of the optimization algorithm is verified to be superior to other algorithms. Secondly, the improved multi-objective optimization algorithm and data-driven model are used to optimize the tread coordinates and obtain an optimized profile. The vehicle dynamics performance of the optimized profile and the wheel wear evolution after long-term service are compared. The results show that the tread wear index of the left and right wheels in a straight line is reduced by 62.4% and 62.6%, respectively, and the wear index of the left and right wheels in a curved line is reduced by 26.5% and 5.5%, respectively. The stability and curve passing performance of the optimized profile are improved. Under the long-term service conditions of the train, the wear amount of the optimized profile is greatly reduced. After the wear prediction of 200,000 km, the wear amount of the optimized profile is reduced by 60.1%, and it has better curve-passing performance. Full article

With the rapid advancement of urban underground space development, shield tunnel construction has seen a significant increase. However, at the initial launching stage of shield tunnels in shallow-buried weak strata, engineering risks such as face instability and sudden surface settlement frequently occur. At present, there are relatively few studies on the reinforcement technology of the initial section of shield tunnel in shallow soft ground and the evolution law of ground disturbance. This study takes the launching section of the Guanggang New City depot access tunnel on Guangzhou Metro Line 10 as the engineering background. By applying MIDAS/GTS numerical simulation, settlement monitoring, and theoretical analysis, the reinforcement technology at the tunnel face, the spatiotemporal evolution of ground settlement, and the mechanism of soil disturbance transmission during the launching process in muddy soil layer are revealed. The results show that: (1) the reinforcement scheme combining replacement filling, high-pressure jet grouting piles, and soil overburden counterpressure significantly improves surface settlement control. The primary influence zone is concentrated directly above the shield machine and in the forward excavation area. (2) When the shield machine reaches the junction between the reinforced and unreinforced zones, a large settlement area forms, with the maximum ground settlement reaching −26.94 mm. During excavation in the unreinforced zone, ground deformation mainly occurs beneath the rear reinforced section, with subsidence at the crown and uplift at the invert. (3) The transverse settlement trough exhibits a typical Gaussian distribution and the discrepancy between the measured maximum settlement and the numerical and theoretical values is only 3.33% and 1.76%, respectively. (4) The longitudinal settlement follows a trend of initial increase, subsequent decrease, and gradual stabilization, reaching a maximum when the excavation passes directly beneath the monitoring point. The findings can provide theoretical reference and engineering guidance for similar projects. Full article