Low-frequency Modulation Research Articles

Synchronous DTC for torque sub-harmonic reduction in low switching frequency induction motor drives

A direct torque control (DTC) algorithm with synchronous modulation for high-power induction motors is presented in this paper. While maintaining the dynamic response and robustness of a PI-based DTC operating in the stationary reference frame, the proposed scheme is able to keep an integer PWM modulation ratio, adjusting the stator flux angle and the switching period at each control step so that the synchronicity condition is always satisfied. In this way, it is possible to achieve an improvement of the very low-frequency harmonic spectrum of the torque, in particular by reducing torque sub-harmonics. These represent one of the main problems associated with low-frequency modulation typical of high-power drives and their reduction allows to avoid drawbacks such as resonance and mechanical stresses. The performance of the proposed algorithm is evaluated with experimental tests on a small-scale test bench.

Accelerating T1 relaxation time measurements of noble gas using transverse low-frequency square-wave magnetic field modulation.

The longitudinal relaxation time (T1) of noble gas nuclear spins is a critical parameter for evaluating the performance of an atomic comagnetometer, significantly influencing the signal-to-noise ratio of the system. Traditional measurement techniques, such as the free induction decay method combined with the spin growth technique (FIDSG), are time-consuming for gases with extended T1 durations, such as 21Ne, and are prone to substantial environmental variability. Here, we propose the transverse low-frequency square-wave magnetic field modulation (LSMM) method for the rapid measurement of T1. The experiment indicates that the LSMM significantly condenses the measurement time to 19.2% of the original, thereby diminishing the robustness demands of the system. Although a minor discrepancy of up to 3 min (or 1.3%) exists between LSMM and FIDSG results, the LSMM method provides strong support for calibrating the performance of comagnetometer cells and conducting various nuclear spin polarization experiments, thereby improving efficiency and reducing energy loss.

Anticipatory and evoked visual cortical dynamics of voluntary temporal attention.

We can often anticipate the precise moment when a stimulus will be relevant for our behavioral goals. Voluntary temporal attention, the prioritization of sensory information at task-relevant time points, enhances visual perception. However, the neural mechanisms of voluntary temporal attention have not been isolated from those of temporal expectation, which reflects timing predictability rather than relevance. Here we use time-resolved steady-state visual evoked responses (SSVER) to investigate how temporal attention dynamically modulates visual activity when temporal expectation is controlled. We recorded magnetoencephalography while participants directed temporal attention to one of two sequential grating targets with predictable timing. Meanwhile, a co-localized SSVER probe continuously tracked visual cortical modulations both before and after the target stimuli. We find that in the pre-target period, the SSVER gradually ramps up as the targets approach, reflecting temporal expectation. Furthermore, we find a low-frequency modulation of the SSVER, which shifts approximately half a cycle in phase according to which target is attended. In the post-target period, temporal attention to the first target transiently modulates the SSVER shortly after target onset. Thus, temporal attention dynamically modulates visual cortical responses via both periodic pre-target and transient post-target mechanisms to prioritize sensory information at precise moments.

Deep Learning-Based Network Security Situation Prediction for Sensor-Enabled Networks

Aims and background: Network security detection has become increasingly complex due to the proliferation of Internet nodes and the ever-changing nature of network architecture. To address this, a multi-layer feedforward neural-network has been employed to construct a model for security threat detection, which has enhanced network security protection. Objectives and Methods: Improving prediction accuracy and real-time performance, this research suggests an optimal strategy based on Clockwork Recurrent-Neural-Networks(CW-RNNs) to handle nonlinearity and temporal dynamics in network security circumstances. We get the model to pick up on both the short-term and long-term temporal aspects of network-security situations by using the clock-cycle RNN. To further improve the network security scenario prediction model, we tune the network hyperparameters using the Grey-Wolf-Optimization(GWO) technique. By incorporating a clock-cycle for hidden units, the model can improve its pattern recognition capabilities by learning short-term knowledge from high-frequency update modules and preserving long-term memory from low-frequency update modules. Results: The optimized clock-cycle RNN achieves better prediction accuracy than competing network models when it comes to extracting nonlinear and temporal characteristics of network security scenarios, according to the experimental data. Conclusions: In addition, our method is perfect for tracking massive amounts of data transmitted by sensor networks because of its minimal time complexity and outstanding real-time performance.

A Novel Modular Multilevel Converter Topology with High- and Low-Frequency Modules and Its Modulation Strategy

To resolve the issue of the difficultly in effectively balancing the output performance improvement, cost reduction, and efficiency improvement of a medium-voltage modular multilevel converter (MMC), a novel MMC (NMMC) topology based on high- and low-frequency hybrid modulation is proposed in this study. Each arm of the NMMC contains a high-frequency sub-module composed of a heterogeneous cross-connect module (HCCM) and N − 1 low-frequency sub-modules composed of half-bridge converters. The high-frequency bridge arm of the HCCM in this study adopts SiC MOSFET devices, while the commutation bridge arm and low-frequency sub-module of the HCCM adopt Si IGBT devices. For the NMMC topology, this study adopts a high/low-frequency hybrid modulation strategy, which gives full play to the advantages of low switching loss in SiC MOSFET devices and low on-state loss in Si IGBT devices. In addition, a specific capacitor voltage balance strategy is proposed for the HCCM, and the working state of the HCCM is analyzed in detail. Furthermore, the feasibility and effectiveness of the proposed topology, modulation strategy, and voltage balancing strategy are verified by experiments. Finally, the proposed topology is compared with the existing MMC topology in terms of device cost and operating loss, which proves that the proposed topology can better balance the cost and efficiency indicators of the device.

Wake flow behind a transversely rotating sphere confined in a pipe at low Reynolds numbers

Direct numerical simulations are performed to investigate the flow past a transversely rotating sphere confined in a pipe. Three sphere diameters of d=0.2D, 0.5D, and 0.8D (D is the pipe diameter) and sphere Reynolds numbers (based on the sphere cross-sectional mean velocity and d) of Res=250–500 are considered. The simulation results highlight the combined effects of the blockage ratio (BR=d/D) and the nondimensionalized rotation rate Ω in the range of 0.2–1.2 on the wake flow. For each BR, with increasing Res and Ω, the wake flow undergoes a transition of the flow pattern from steady symmetry and unsteady symmetry to unsteady asymmetry. For BR=0.2, the variation in flow behaviors with Ω is similar to those reported in the previous studies on a transversely rotating sphere subjected to a uniform flow. With increasing BR from 0.2 to 0.5, the unsteady asymmetric wake flow is characterized by distorted near-wake vortex rings and a series of staggered inward rolled-up vortex arcs on the double streamwise vortex threads, which results in a low-frequency modulation of the unsteady wake flow. These rolled-up vortex arcs are connected with downstream quasi-streamwise vortices and form hairpin-like vortices. Dynamic Mode Decomposition (DMD) analysis shows that the distorted near-wake vortex rings are associated with the antisymmetric DMD mode at the adjacent frequency around the symmetric primary DMD mode. With BR=0.8, there is a drastic increase in the sphere's force coefficients. A more complex wake flow behavior is found due to a strong interaction between the wake flow and the near-pipe-wall flow. At Ω=1.2, dominant asymmetric flow structures are characterized by impingement of the vortex filaments. The low-frequency modulation of these wake structures is also analyzed using the DMD analysis.

Comprehensive measurement of three-dimensional thermal conductivity tensor using a beam-offset square-pulsed source (BO-SPS) approach

Accurately measuring the three-dimensional thermal conductivity tensor is essential for understanding and engineering the thermal behavior of anisotropic materials. Existing methods often struggle to isolate individual tensor elements, leading to large measurement uncertainties and time-consuming iterative fitting procedures. In this study, we introduce the Beam-Offset Square-Pulsed Source (BO-SPS) method for comprehensive measurements of three-dimensional anisotropic thermal conductivity tensors. This method uses square-pulsed heating and precise temperature rise measurements to achieve high signal-to-noise ratios, even with large beam offsets and low modulation frequencies, enabling the isolation of thermal conductivity tensor elements. We demonstrate and validate the BO-SPS method by measuring X-cut and AT-cut quartz samples. For X-cut quartz, with a known relationship between in-plane and cross-plane thermal conductivities, we can determine the full thermal conductivity tensor and heat capacity simultaneously. For AT-cut quartz, assuming a known heat capacity, we can determine the entire anisotropic thermal conductivity tensor, even with finite off-diagonal elements. Our results yield consistent principal thermal conductivity values for both quartz types, demonstrating the method's reliability and accuracy. This research highlights the BO-SPS method's potential to advance the understanding of thermal behavior in complex materials.

Study of the influence of the technological mode of ultrasonic pressing with low-frequency modulation on the sructure of polytetrafluoroethylene modified with boron nintiride

Study of the influence of the technological mode of ultrasonic pressing with low-frequency modulation on the sructure of polytetrafluoroethylene modified with boron nintiride

Interannual Fluctuations and Their Low-Frequency Modulation of Summertime Heavy Daily Rainfall Potential in Western Japan

Heavy rainfall under the conditions of the changing climate has recently garnered considerable attention. The statistics on heavy daily rainfall offer vital information for assessing present and future extreme events and for clarifying the impacts of global climate variability and change, working to form a favorable background. By analyzing a set of large-ensemble simulations using a global atmospheric model, this study demonstrated that two different physical processes in global climate variability control the interannual fluctuations in the 99th- and 90th-percentile values of summertime daily rainfall (i.e., the potential amounts) on Kyushu Island in western Japan. The 90th-percentile values were closely related to large-scale horizontal moisture transport anomalies due to changes in the subtropical high in the northwestern Pacific, which was usually accompanied by basin-scale warming in the Indian Ocean subsequent to the wintertime El Niño events. The contributions of the sea surface temperatures over the northern Indian Ocean and the eastern tropical Pacific Ocean showed low-frequency modulations, mainly due to the influences of the global warming tendency and the interdecadal variability in the climate system, respectively. In contrast, tropical cyclone activity played a major role in changing the 99th-percentile value. The potentials of both the tropical cyclone intensity and the existence density fluctuated, largely owing to the summertime sea surface temperature over the tropical Pacific, which can be modulated by the El Niño diversity on interdecadal timescales.

CrowdAlign: Shared-weight dual-level alignment fusion for RGB-T crowd counting

The combination of visible and thermal images has been proven to be effective in improving accuracy for crowd counting in illumination-unconstrained scenes. However, the challenging problem of misalignment in RGB-T image pairs has not been extensively explored in this context. This study aims to address the issue of misalignment between RGB and thermal image pairs to enhance the counting accuracy of cross-modal models. Specifically, we propose CrowdAlign, a cross-modal feature alignment fusion network that utilizes a shared-weight strategy for efficient feature extraction. Additionally, CrowdAlign addresses alignment adjustments through two stages: pre-fusion and post-fusion alignment. For pre-fusion feature extraction, we design a dual-level spatial-semantic parallel alignment module, while for post-fusion feature extraction, a low-frequency feature attention filtering module is developed. This two-stage alignment approach enables cross-modal feature alignment without requiring additional supervision. Experiments on the public benchmarks demonstrate that our method is effective under RGB-T misalignment or dark conditions. We hope CrowdAlign will inspire researchers to focus on and explore the issue of misalignment between RGB image and thermal image for cross-modal crowd counting.

Single-beam low-frequency loss modulation technique for two-photon absorption measurement

We present a straightforward and reliable single-beam configuration designed for the assessment of two-photon absorption (2PA) through the utilization of the loss modulation technique. Mechanical rotation of a half-wave plate induces a sinusoidal modulation in the envelope of the probe pulse train. The elimination of spurious signals is achieved by determining the difference of the lock-in amplifier output at the focused and defocused positions of the sample. Our findings, based on measurements with dye solutions and crystalline silicon, demonstrate the feasibility of determining the 2PA coefficient, subject to preliminary calibration of the setup with reference samples. Remarkably, the acquisition of the 2PA signal in silicon at 1030 nm is accomplished with less than 200 pJ energy of the laser pulse, overcoming the challenge posed by concurrent linear absorption. Additionally, a signal of 3PA is revealed despite the presence of 2PA and linear absorption.

Low-frequency Acoustic Collimation Modulation Based on Monopole Mie Resonance Acoustic Metamaterials

Acoustic metamaterials show great flexibility in manipulating acoustic waves and exhibit important applications. However, an increasing number of applications are suitable for the low-frequency range, which makes it challenging to design acoustic metamaterials for low-frequency modulation. Here, we propose a subwavelength monopole Mie resonance acoustic metamaterial that can flexibly control the propagation route of acoustic waves. Compared to the background medium, the designed Mie unit has a higher refractive index and can achieve directional manipulation of low-frequency acoustic waves based on monopole Mie resonance. Furthermore, an array formed by multiple Mie units in a specific arrangement can achieve the acoustic collimation phenomenon. The designed monopole Mie resonance acoustic metamaterial has potential application prospects in fields such as low-frequency filtering, noise suppression, and nondestructive testing.

Exploring advanced 2D acquisitions in breast tomosynthesis: T-shaped and Pentagon geometries.

In this study, we investigate the performance of advanced 2D acquisition geometries - Pentagon and T-shaped - in digital breast tomosynthesis (DBT) and compare them against the conventional 1D geometry. Unlike the conventional approach, our proposed 2D geometries also incorporate anterior projections away from the chest wall. Implemented on the Next-Generation Tomosynthesis (NGT) prototype developed by X-ray Physics Lab (XPL), UPenn, we utilized various phantoms to compare three geometries: a Defrise slab phantom with alternating plastic slabs to study low-frequency modulation; a Checkerboard breast phantom (a 2D adaptation of the Defrise phantom design) to study the ability to reconstruct the fine features of the checkerboard squares; and the 360° Star-pattern phantom to assess aliasing and compute the Fourier-spectral distortion (FSD) metric that assesses spectral leakage and the contrast transfer function. We find that both Pentagon and T-shaped scans provide greater modulation amplitude of the Defrise phantom slabs and better resolve the squares of the Checkerboard phantom against the conventional scan. Notably, the Pentagon geometry exhibited a significant reduction in aliasing of spatial frequencies oriented in the right-left (RL) medio-lateral direction, which was corroborated by a near complete elimination of spectral leakage in the FSD plot. Conversely T-shaped scan redistributes the aliasing between both posteroanterior (PA) and RL directions thus maintaining non-inferiority against the conventional scan which is predominantly affected by PA aliasing. The results of this study underscore the potential of incorporating advanced 2D geometries in DBT systems, offering marked improvements in imaging performance over the conventional 1D approach.

Low-Frequency Intensity Modulation of High-Frequency Rotor Noise

Acoustic spectra of rotor noise yield frequency distributions of energy within pressure time series. However, they are unable to reveal phase relations between different frequency components while these play a role in the fundamental understanding of low-frequency intensity modulation of higher-frequency rotor noise. A methodology to quantify interfrequency modulation is applied to a comprehensive acoustic dataset of a fixed-pitch benchmark rotor, operating at a low Reynolds number and at advance ratios ranging from J=0 to 0.61. Our findings strengthen earlier observations in case of a hovering rotor, in which the modulation of the high-frequency noise is strongest around an elevation angle of θ=−20° (below the rotor plane). For the nonzero advance ratios, modulation becomes dominant in the sector −45°≲θ≲0° and is most pronounced at the highest advance ratio tested (J=0.61). Intensity modulation of high-frequency noise is primarily the consequence of a far-field observer experiencing a cyclic sweep through the noise directivity pattern of relatively directive trailing-edge noise. This noise component becomes more intense with increasing J and is associated with broadband features of the partially separated flow over the rotor blades.

Clustered Voltage Control and Modulation Scheme With Switching Loss Reduction for High Power Hybrid Cascaded Converter

The hybrid cascade converters (HCC) is a potential solution to achieve harmonic current compensation in medium and high voltage applications due to the characteristics of having high frequency module. However, the high switching frequency inevitably leads to an increase of undesirable switching loss. In addition, since the reduction of power loss and the balance of clustered voltage are mutually interrelated, the existing modulation and control schemes cannot cope with them decently. To address this problem, the HCC is divided into a high-frequency module (HFM) and a low-frequency module (LFM), and a corresponding hybrid modulation scheme is proposed to reduce the power loss while maintaining a high harmonic compensation performance. Then, based on the analysis of the system voltage constraints, the dc-link voltage and threshold voltage under different parameters are redesigned. Furthermore, since the power flow between modules has been changed with the hybrid modulation scheme, the conventional clustered voltage control strategy is not capable of clustered control. Therefore, based on the re-modeling of the power flow, a negative-sequence voltage injection control strategy is proposed to achieve voltage balance. Finally, simulation and experimental results are demonstrated to verify the effectiveness of the proposed scheme.

Frequency shift of parametric sound by face-to-face pair of sources in relative motion.

This paper reports an acoustic phenomenon regarding a parametric sound source (also referred to as a parametric array): a secondary sound wave is generated from the nonlinear interaction of multiple primary sound waves with varied frequency components, particularly when two relatively moving sound sources face each other. It was found that the frequency of the secondary wave fluctuated according to the source movement and provided a theoretical explanation for this phenomenon. It is experimentally demonstrated that this frequency shift was approximately proportional to the velocity of the moving source toward the fixed source and to the driving frequency of the moving source. This phenomenon has much in common with the Doppler's effect, but its unique property is that the frequency shift depends on neither the observation position nor the source velocity toward the observer. These sound generation principles enable measurement of the velocity of slowly moving sound sources while maintaining a low-modulation frequency band and a short measurement time. This phenomenon can potentially be applied to an alternative approach for acoustic noncontact velocimetry of moving objects.

Association of body-mass index with physiological brain pulsations across adulthood – a fast fMRI study

Background/objectiveObesity is a risk factor for several brain-related health issues, and high body-mass index (BMI) is associated with an increased risk for several neurological conditions, including cognitive decline and dementia. Cardiovascular, respiratory, and vasomotor brain pulsations have each been shown to drive intracranial cerebrovascular fluid (CSF) flow, which is linked to the brain metabolite efflux that sustains homeostasis. While these three physiological pulsations are demonstrably altered in numerous brain diseases, there is no previous investigation of the association between physiological brain pulsations and BMI.Subjects/methodsWe measured the amplitudes of the physiological brain pulsations using amplitude of low frequency fluctation (ALFF) based method with resting-state functional magnetic resonance imaging via high temporal resolution whole-brain magnetic resonance encephalography (MREG) in 115 healthy subjects. We next undertook multiple linear regression to model the BMI effect voxel-wise whole-brain on very low frequency (VLF), respiration, cardiovascular, and respiratory induced modulation of cardiovascular pulsation amplitudes with age, pulse pressure, and gender as nuisance variables.ResultsIn our study population, BMI was positively associated with the amplitudes of vasomotor, respiratory, and respiratory induced modulations of cardiovascular pulsations (p < 0.05), while negatively associated with the amplitudes of cardiovascular pulsations (p < 0.05).ConclusionsThe findings suggest that BMI is a significant factor in alterations of cardiovascular pulsation of neurofluids. As physiological pulsations are the drivers of CSF flow and subsequent metabolite clearance, these results emphasize the need for further research into the mechanisms through which obesity affects brain clearance.

Analytical and numerical modeling of nonlinear lamb wave interaction with a breathing crack with low-frequency modulation

To characterize fatigue crack, an analytical calculation and finite element (FE) simulation of Lamb wave propagating through the region of a breathing crack in a two-dimensional(2D) isotropic plate were studied. Contact surface boundary conditions between the two surfaces of the vertical crack were considered to study contact acoustic nonlinearity (CAN) from the breathing contact crack in conjunction with the modal decomposition method, Fourier transform, and variational principle-based algorithm. Reflection and transmission coefficients in the fundamental frequency and second harmonic frequency were calculated and analyzed quantitatively. Different ratios of incident wave amplitude to crack width were studied to calculate CAN results related to micro-crack width. In addition, a low-frequency (LF) vibration(10 Hz) excitation was introduced to perturb the free surface vertical crack to close, and an interrogating Lamb wave(1 MHz) was used to study crack-related CAN in different conditions for interpreting the modulation mechanism. The contact boundary conditions between two surfaces of vertical crack were set which were dynamically changed due to the low frequency modulation. The clapping effects when the crack closed due to the modulation of the contact boundary conditions between the crack surfaces were studied and analyzed to get the quantitative correlation between CAN and LF modulation. The results obtained from the analytical model were compared with those from the FE simulation, showing good consistency. Knowledge of these effects is essential to correctly gauge the severity of surface cracks in the plate, which can be spotlighted in its application to quantitative evaluation of micro fatigue cracks in structural health monitoring(SHM).

Optimized low switching frequency modulation with neutral point voltage control for three-level converters

Optimized low switching frequency modulation with neutral point voltage control for three-level converters

3D-MRI super-resolution reconstruction using multi-modality based on multi-resolution CNN

Background and ObjectiveHigh-resolution (HR) MR images provide rich structural detail to assist physicians in clinical diagnosis and treatment plan. However, it is arduous to acquire HR MRI due to equipment limitations, scanning time or patient comfort. Instead, HR MRI could be obtained through a number of computer assisted post-processing methods that have proven to be effective and reliable. This paper aims to develop a convolutional neural network (CNN) based super-resolution reconstruction framework for low-resolution (LR) T2w images. MethodIn this paper, we propose a novel multi-modal HR MRI generation framework based on deep learning techniques. Specifically, we construct a CNN based on multi-resolution analysis to learn an end-to-end mapping between LR T2w and HR T2w, where HR T1w is fed into the network to offer detailed a priori information to help generate HR T2w. Furthermore, a low-frequency filtering module is introduced to filter out the interference from HR-T1w during high-frequency information extraction. Based on the idea of multi-resolution analysis, detailed features extracted from HR T1w and LR T2w are fused at two scales in the network and then HR T2w is reconstructed by upsampling and dense connectivity module. ResultsExtensive quantitative and qualitative evaluations demonstrate that the proposed method enhances the recovered HR T2w details and outperforms other state-of-the-art methods. In addition, the experimental results also suggest that our network has a lightweight structure and favorable generalization performance. ConclusionThe results show that the proposed method is capable of reconstructing HR T2w with higher accuracy. Meanwhile, the super-resolution reconstruction results on other dataset illustrate the excellent generalization ability of the method.