Conventional Compensation Research Articles

Solute Diffusivity and Local Free Volume in Cross-Linked Polymer Network: Implication of Optimizing the Conductivity of Polymer Electrolyte.

The diffusion of small molecules or ions within polymeric materials is critical for their applications, such as polymer electrolytes. Cross-linking has been one of the common strategies to modulate solute diffusivity and a polymer’s mechanical properties. However, various studies have shown different effects of cross-linking on altering the solute transports. Here, we utilized coarse-grained molecular dynamics simulation to systematically analyze the effects of cross-linking and polymer rigidity of solute diffusive behaviors. Above the glass transition temperature , the solute diffusion followed the Vogel–Tammann–Fulcher (VTF) equation, D = D e. Other than the conventional compensation relation between the activation energy and the pre-exponential factor D, we also identified a correlation between and Vogel temperature T. We further characterized an empirical relation between T and cross-linking density. Integrating the newly identified correlations among the VTF parameters, we formulated a relation between solute diffusion and the cross-linking density. The combined results proposed the criteria for the optimal solute diffusivity in cross-linked polymers, providing generic guidance for novel polymer electrolyte design.

A force-insensitive impedance compensation method for giant magnetostriction ultrasonic cutting system of Nomex honeycomb composites

The high-quality machining of Nomex honeycomb composites is challenging due to its intrinsic brittleness. The rotary ultrasonic cutting performed on Giant magnetostriction ultrasonic system (GMUS) has been recognized as a superior method for the high-quality machining of Nomex honeycomb, owing to its capability to generate large-amplitude ultrasonic tool vibration. The stability of ultrasonic tool vibration plays a critical role in guaranteeing the acceptable surface quality of Nomex workpiece. However, the unique inhomogeneity of honeycomb induces time-varying cutting force, which can violate the stability of ultrasonic tool vibration using conventional compensation methods. In this study, a force-insensitive impedance compensation (FIC) method was proposed to improve the vibration stability of GMUS for honeycomb machining. A theoretical model which describes the vibration characteristics of GMUS was developed to calculate the optimum compensation impedance to adapt the time-varying cutting force. Experimental tests were conducted on Nomex honeycomb composite to evaluate the performance of proposed FIC method by inspecting the surface quality of machined workpiece. The experimental results demonstrated that the compensated ultrasonic cutting system showed an enhanced vibration stability during the machining of Nomex honeycomb composite. Compared with conventional compensation method, the honeycomb processed by GMUS with the FIC method showed much fewer cell collapses.

Weak Grid-Induced Stability Problems and Solutions of Distributed Static Compensators with Voltage Droop Support

Distributed static compensators (DSTATCOMs) are grid-connected power electronic equipment dedicated to compensating reactive power as well as improving voltage regulation in distribution networks. They eclipse conventional compensation approaches, such as capacitor banks, in terms of flexibility and effectiveness. Despite their identified advantages, STATCOMs with voltage droop are subject to weak grid-induced stability problems, as first revealed by this paper. Specifically, the voltage droop controller that couples the amplitude of point of common coupling (PCC) voltages to the reactive current reference creates a local control loop. Such a loop greatly deteriorates system stability in weak grids, which feature large and variable grid impedances. To address such stability problems, we propose a novel virtual resistance control scheme, which improves system stability through mitigation of local control loop gains in the low-frequency band. Experimental results obtained from a DSTATCOM prototype clearly demonstrate the correctness of stability analysis and the effectiveness of stability improvement.

Active Power Filters in Aircraft Electric Power Systems: A Comparison Among Conventional and Advanced Compensation Techniques

The world is moving towards more electric aircraft due to its benefits for more efficiency and less dependence on conventional energy. However, as conventional energy has its drawback of reduced total energy efficiency for aircraft, the use of more electronics is accountable for higher losses, unbalance currents, reduced power supply performance, and generation of harmonics. In this paper, a comparison among three conventional control techniques (Synchronous Rotating Frame, Sinusoidal Current Control and Constant Instantaneous Power Control) and advanced control techniques (ANN, fuzzy logic controller, genetic algorithm, adaptive blanket body cover algorithm, the combination of ANN & fuzzy logic controller and ANN with the application of genetic & adaptive blanket body search algorithm) for aircraft shunt active power filter has been proposed. Furthermore, the best control schemes for aircraft active power filters will be proposed to depend upon the THD of source current and voltage and the compensation time (speed).

Improvement of voltage stability for grid connected solar photovoltaic systems using static synchronous compensator with recurrent neural network

Purpose. This article proposes a new control strategy for static synchronous compensator in utility grid system. The proposed photovoltaic fed static synchronous compensator is utilized along with recurrent neural network based reference voltage generation is presented in grid system network. The novelty of the proposed work consists in presenting a Landsman converter enhanced photovoltaic fed static synchronous compensator with recurrent neural network algorithm, to generate voltage and maintain the voltage-gain ratio. Methods. The proposed algorithm which provides sophisticated and cost-effective solution for utilization of adaptive neuro-fuzzy inference system as maximum power point tracking assures controlled output and supports the extraction of complete power from the photovoltaic panel. Grid is interconnected with solar power, voltage phase angle mismatch, harmonic and voltage instability may occur in the distribution grid. The proposed control technique strategy is validated using MATLAB/Simulink software and hardware model to analysis the working performances. Results. The results obtained show that the power quality issue, the proposed system to overcome through elimination of harmonics, reference current generation is necessary, which is accomplished by recurrent neural network. By recurrent neural network, the reference signal is generated more accurately and accordingly the pulses are generated for controlling the inverter. Originality. Compensation of power quality issues, grid stability and harmonic reduction in distribution network by using photovoltaic fed static synchronous compensator is utilized along with recurrent neural network controller. Practical value. The work concerns the comparative study and the application of static synchronous compensator with recurrent neural network controller to achieve a good performance control system of the distribution network system. This article presents a comparative study between the conventional static synchronous compensator, static synchronous compensator with recurrent neural network and hardware implementation with different load. The strategy based on the use of a static synchronous compensator with recurrent neural network algorithm for the control of the continuous voltage stability and harmonic for the distribution network-linear as well as non-linear loads in efficient manner. The study is validated by the simulation results based on MATLAB/Simulink software and hardware model.

Elastic dosage compensation by X-chromosome upregulation

X-chromosome inactivation and X-upregulation are the fundamental modes of chromosome-wide gene regulation that collectively achieve dosage compensation in mammals, but the regulatory link between the two remains elusive and the X-upregulation dynamics are unknown. Here, we use allele-resolved single-cell RNA-seq combined with chromatin accessibility profiling and finely dissect their separate effects on RNA levels during mouse development. Surprisingly, we uncover that X-upregulation elastically tunes expression dosage in a sex- and lineage-specific manner, and moreover along varying degrees of X-inactivation progression. Male blastomeres achieve X-upregulation upon zygotic genome activation while females experience two distinct waves of upregulation, upon imprinted and random X-inactivation; and ablation of Xist impedes female X-upregulation. Female cells carrying two active X chromosomes lack upregulation, yet their collective RNA output exceeds that of a single hyperactive allele. Importantly, this conflicts the conventional dosage compensation model in which naïve female cells are initially subject to biallelic X-upregulation followed by X-inactivation of one allele to correct the X dosage. Together, our study provides key insights to the chain of events of dosage compensation, explaining how transcript copy numbers can remain remarkably stable across developmental windows wherein severe dose imbalance would otherwise be experienced by the cell.

Inversion-based attenuation compensation with dip constraint

Instability is an inherent problem with the attenuation compensation methods and has been partially relieved by using the inverse scheme. However, the conventional inversion-based attenuation compensation approaches ignore the important prior information of the seismic dip. Thus, the compensated result appears to be distorted spatial continuity and has a low signal-to-noise ratio (S/N). To alleviate this issue, we have incorporated the seismic dip information into the inversion framework and have developed a dip-constrained attenuation compensation (DCAC) algorithm. The seismic dip information, calculated from the poststack seismic data, is the key to construct a dip constraint term. Benefiting from the introduction of the seismic dip constraint, the DCAC approach maintains the numerical stability and preserves the spatial continuity of the compensated result. Synthetic and field data examples demonstrate that the proposed method can not only improve seismic resolution, but also protect the continuity of seismic data.

An Optimal Zero-Sequence Voltage Injection Strategy for DVR Under Asymmetric Sag

This article introduces an optimal zero-sequence voltage injection strategy (OZVIS) for the three-phase dynamic voltage restorer (DVR), which can effectively reduce the output voltage magnitude of DVR in case of asymmetric sags in a three-phase, three-wire power system, so as to improve the compensation capacity of the device. The conventional compensation strategy improves the active power or reduces the voltage amplitude of the DVR through phase rotation, but the two functions are difficult to achieve together. In this article, the operation principle of OZVIS is first introduced. Then, the optimality and effectiveness of the strategy are theoretically demonstrated by means of a plane geometric modeling approach. In addition, the reduction extent using OZVIS in different voltage sag types is quantified, which is based on the minimum energy compensation strategy. Furthermore, a digital “plug-in” algorithm implementation for the proposed strategy is elaborated. Finally, the experimental results will be shown to verify the feasibility and effectiveness of OZVIS under an asymmetric situation. Moreover, the adaptability under a symmetric situation will also be illustrated.

Application of Novel AC–AC Matrix VFD for Power Factor Improvement in Conventional AC–DC–AC VFD-Loaded Power Distribution Lines

In this study, an innovative approach to matrix-converter-based AC-–AC variable frequency drives (VFDs) is introduced. The possibility of using AC–AC matrix VFDs for reactive power compensation in conventional AC–DC–AC VFD-loaded power distribution lines is investigated. It is found that the interaction of a large number of conventional AC–DC–AC VFDs with a conventional capacitor-based local compensation device leads to overcompensation in 0.4 kV power distribution lines. This is due to the fact that the conventional compensation device is designed to compensate the lagging reactive power produced by inductive loads, such as AC motors. This highlights the demand for the compensation of leading reactive power that is not predicted by the designer. To solve this problem, the modification of a certain number of previously installed VFDs by replacing their conventional AC–DC–AC converters with AC–AC matrix converters is proposed. This can lead to improvements in the power factor in 0.4 kV power distribution lines. In this study, the range of reactive power produced by conventional AC–DC–AC VFDs was determined mathematically, by simulation, and experimentally. The range of reactive power produced by the novel AC–AC matrix VFD was also determined. On that basis, the number of VFDs to be modified is defined to keep the power factor close to unity.

Temperature variation compensated damage classification and localisation in ultrasonic guided wave SHM using self-learnt features and Gaussian mixture models

Conventional damage localisation algorithms used in ultrasonic guided wave-based structural health monitoring (GW-SHM) rely on physics-defined features of GW signals. In addition to requiring domain knowledge of the interaction of various GW modes with various types of damages, they also suffer from errors due to variations in environmental and operating conditions (EOCs) in practical use cases. While several machine learning tools have been reported for EOC compensation, they need to be custom-designed for each combination of damage and structure due to their dependence on physics-defined feature extraction. In this work, we propose a convolutional neural network (CNN)-based automated feature extraction framework coupled with Gaussian mixture model (GMM) based temperature compensation and damage classification and localisation method. Features learnt by the CNNs are used for damage classification and localisation of damage by modelling the probability distribution of the features using GMMs. The Kullback–Leibler (KL) divergence of these GMMs with respect to corresponding baseline GMMs are used as signal difference coefficients to compute damage indices (DIs) along various GW sensor paths, and thus for damage localisation. The efficacy of the proposed method is demonstrated using FE generated GW-data for an aluminium plate with a network of six lead zirconate titanate (PZT) sensors, for three different types of damages (rivet hole, added mass, notch) at various temperatures (from 0 ∘C to 100 ∘C), with added white noise and pink noise to incorporate errors due to EOCs. We also present experimental validation of the method through characterisation of notch damage in an aluminium panel under varying and non-uniform temperature profiles, using a portable custom-designed field programmable gate array based signal transduction and data acquisition system. We demonstrate that the method outperforms conventional temperature compensation method using GMM with physics-defined features for damage localisation in GW-SHM systems prone to EOC variations.

Atmospheric turbulence compensation for OAM-carrying vortex waves based on convolutional neural network

The helical phasefront and orbital angular momentum (OAM) of vortex electromagnetic waves (VEMW) have attracted extensive attention in expanding communication capacity and enhancing radar imaging resolution. However, the VEMW is sensitive to atmospheric turbulence (AT), which will cause helical phasefront distortion and OAM mode diffusion. Hence, a convolutional neural network (CNN) based method for AT compensation is proposed. Specifically, the developed CNN automatically learns the AT characteristic parameters from the distorted VEMW phasefront and reconstructs the equivalent AT phase screen, and then, compensation is achieved by loading the inverse of the predicted phase on the distorted VEMW. The simulations show that the trained CNN has strong generalization capability and can perform high-quality AT prediction for different turbulence strengths and OAM modes, after compensation, the distorted phase is repaired and the mode purity is significantly improved. Moreover, comparing with the conventional AT compensation method, the proposed method shows smaller computational burdens and higher compensation accuracy.

Improved Cross-coupling Effect Compensation Method for Sensorless Control of IPMSM With High Frequency Voltage Injection

In this paper, the conventional cross-coupling effect compensation method that uses offline measured cross-coupling factor by current compensation in high frequency pulsating voltage injection based sensorless control is firstly extended for use in high frequency rotating voltage injection based sensorless control by angle compensation. Compared with the current compensation method, the angle compensation method has better dynamic performance as confirmed by experiments. To enable direct angle compensation, a novel method for offline measuring the cross-coupling induced errors is proposed by injecting HF voltages in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -axis, respectively. The measured errors can be used for online cross-coupling effect angle compensation irrespective of the injected signal that is used for position estimation. Experiments have verified the effectiveness of the proposed methods. In addition, stability and convergence of sensorless operation with the proposed cross-coupling effect compensation methods at highly saturated conditions are also analyzed and experimentally evaluated.

A High-Precision Motion Errors Compensation Method Based on Sub-Image Reconstruction for HRWS SAR Imaging

High-resolution wide-swath (HRWS) synthetic aperture radar (SAR) plays an important role in remote sensing observation. However, the motion errors caused by the carrier platform’s instability severely degrade the performance of the HRWS SAR imaging. Conventional motion errors compensation methods have two drawbacks, i.e., (1) ignoring the spatial variation of the phase errors of pixels along the range direction of the scene, which leads to lower compensation accuracy, and (2) performing compensation after echo reconstruction, which fails to consider the difference in motion errors between channels, resulting in poor imaging performance in the azimuth direction. In this paper, to overcome these two drawbacks, a high-precision motion errors compensation method based on sub-image reconstruction (SI-MEC) for high-precision HRWS SAR imaging is proposed. The proposed method consists of three steps. Firstly, the motion errors of the platform are estimated by maximizing the intensity of strong points in multiple regions. Secondly, combined with the multichannel geometry, the equivalent phase centers (EPCs) used for sub-images imaging are corrected and the sub-images imaging is performed before reconstruction. Thirdly, the reconstruction is performed by using the sub-images. The proposed method has two advantages, i.e., (1) compensating for the spatially varying phase errors in the range direction, by correcting EPCs, to improve the imaging quality, and (2) compensating for the motion errors of each channel in sub-image imaging before reconstruction, to enhance the imaging quality in the azimuth direction. Moreover, the experimental results are provided to demonstrate that the proposed method outperforms PGA and BP-FMSA.

Power quality improvement in distribution system based on dynamic voltage restorer using PI tuned fuzzy logic controller

Purpose. This article proposes a new control strategy for Dynamic Voltage Restorer (DVR) in utility grid for distribution system. The proposed DVR using PI tuned fuzzy logic scheme is based on replacement of conventional DVR and voltage sag compensation in distribution system network. The novelty of the proposed work consists in presenting an enhanced PI tuned fuzzy logic algorithm to control efficiently the dynamic voltage restorer when voltage sag is suddenly occurred. Methods. The proposed algorithm which provides sophisticated and cost-effective solution for power quality problems. Our strategy is based on tuned fuzzy control of reactive powers and also closed loop for harmonic reduction in distribution system. The proposed control technique strategy is validated using MATLAB / Simulink software to analysis the working performances. Results. The results obtained clearly show that DVR using PI tuned fuzzy logic have good performances (sag compensation, harmonic reduction) compared to conventional DVR. Originality. Compensation of voltage sag/ swell in distribution for reactive power and current harmonic reduction by using DVR based PI tuned fuzzy logic controller. Practical value. The work concerns the comparative study and the application of DVR based on PI tuned fuzzy techniques to achieve a good performance control system of the distribution system. This article presents a comparative study between the conventional DVR control and PI tuned fuzzy DVR control. The strategy based on the use of a PI tuned fuzzy controller algorithm for the control of the continuous voltage sag and harmonic for the distribution network-linear as well as non-linear loads in efficient manner. The study is validated by the simulation results based on MATLAB / Simulink software.

An iterative image-based inter-frame motion compensation method for dynamic brain PET imaging

As a non-invasive imaging tool, positron emission tomography (PET) plays an important role in brain science and disease research. Dynamic acquisition is one way of brain PET imaging. Its wide application in clinical research has often been hindered by practical challenges, such as patient involuntary movement, which could degrade both image quality and the accuracy of the quantification. This is even more obvious in scans of patients with neurodegeneration or mental disorders. Conventional motion compensation methods were either based on images or raw measured data, were shown to be able to reduce the effect of motion on the image quality. As for a dynamic PET scan, motion compensation can be challenging as tracer kinetics and relatively high noise can be present in dynamic frames. In this work, we propose an image-based inter-frame motion compensation approach specifically designed for dynamic brain PET imaging. Our method has an iterative implementation that only requires reconstructed images, based on which the inter-frame subject movement can be estimated and compensated. The method utilized tracer-specific kinetic modelling and can deal with simple and complex movement patterns. The synthesized phantom study showed that the proposed method can compensate for the simulated motion in scans with 18F-FDG, 18F-Fallypride and 18F-AV45. Fifteen dynamic 18F-FDG patient scans with motion artifacts were also processed. The quality of the recovered image was superior to the one of the non-corrected images and the corrected images with other image-based methods. The proposed method enables retrospective image quality control for dynamic brain PET imaging, hence facilitating the applications of dynamic PET in clinics and research.

An Improved Aeromagnetic Compensation Method Robust to Geomagnetic Gradient

Aeromagnetic surveys play an important role in many fields, for example, archaeology, anti-submarine warfare, and geophysical exploration. Being in the geomagnetic field, the aircraft generates a great deal of magnetic interference, resulting in bad performance during detection surveys. Thus, it is necessary and important to perform aeromagnetic compensation in advance. Conventional aeromagnetic compensation methods consider that the geomagnetic gradient is approximately zero after bandpass filtering, bringing about the inaccuracy of compensation coefficients. To address this issue, an improved aeromagnetic compensation method robust to geomagnetic gradient is proposed. In this study, the International Geomagnetic Reference Field (IGRF) model was employed to model the geomagnetic gradient. Then, the estimated geomagnetic gradient was subtracted from the measured data, which improved the accuracy of the compensation equations. Field experiments were conducted to verify the effectiveness of the proposed method. The experimental results show that compared to the traditional method, the compensation performance of the proposed method was improved by 152% to 329%. For the level flight, the standard deviation of residual noise after compensation can be as low as 3.3pT. The results indicate that the proposed method can significantly improve the compensation effect, showing great benefits for weak magnetic anomaly detection.

Broadband angular dispersion compensation for digital micromirror devices.

In this Letter, we present a compact broadband angular dispersion compensation method for digital micromirror devices (DMDs) and ultrashort pulse lasers, which effectively extends the conventional single-wavelength compensation design to a wide wavelength range of 300 nm. First, a parametric model was developed for the dispersion compensation unit, consisting of a transmission grating and a 4f telescope sub-unit, to guide the selection of components and parameter optimization for broadband applications. In the experiments, we designed a single slit-based metrology system to measure and quantify the compensated angular dispersion of a Ti:sapphire femtosecond laser with a pulse width of 75 fs. The results indicate that our method can reduce the angular dispersion to 0.04°, i.e., pulse widening less than 20 fs, over a wavelength range of 750-1050 nm. To demonstrate this, the DMD system was used as a multi-wavelength beam shaper to reconstruct a wavefront that contains the "CUHK" pattern and the results confirmed its ability to provide effective broadband angular dispersion compensation. This means the DMD can be used in different applications that employ a broadband light source, e.g., wavelength tunable femtosecond laser, attosecond laser, supercontinuum laser, and multi-color LED.

Optimization of Nano-Topography Distribution by Compensation Grinding

Optical surfaces are required to have high form accuracy and smoothness. The form accuracy must be below 50 nm. Form accuracy is currently on the order of several tens of nanometers or less; however, further improvement is required. To improve form accuracy, compensation grinding is performed based on form measurement results. However, when the form error is small, a small periodical waviness occurs on the ground surface, which is known as nano-topography. This waviness cannot be compensated for using conventional compensation methods because the nano-topography distributions are not reproducible. A previous study showed that grinding conditions affect the spatial frequency of nano-topography. Therefore, in this study, optimum grinding conditions are estimated from the view point of nano-topography distributions, and the grinding conditions are compensated to optimize these distributions.

Type-II Compensation for Automotive Buck Converters Implemented by Fully Integrated Capacitor Multiplier

This paper presents a solution for full integration of a Type-II compensation circuit for DC-DC buck converters. It employs a novel active circuit based on capacitor multiplier, able to emulate the R-series-C ensemble within the conventional Gm-RC compensation network. The proposed solution was used to design a current-mode DC-DC buck converter for automotive applications. The implementation of key circuits in a 180 nm CMOS process is presented in some detail. Simulation results demonstrate that the converter meets all design requirements: it provides a 5 V output voltage over wide ranges of the input voltage, 6 V to 45 V, and load current, between 10 mA and 300 mA. Its frequency and transient responses compare well against the performance of a similar converter that employs a conventional Gm-RC compensation circuit. It consumes 20 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{A}$ </tex-math></inline-formula> more, but requires significantly less die area, than its counterpart. Furthermore, the tuning required to compensate for process and temperature variations is realized by programming the multiplication factor of the capacitor multiplier.

Structure-Guided L1-2 Minimization for Stable Multichannel Seismic Attenuation Compensation

Absorption in subsurface media severely degrades seismic data quality. Seismic attenuation compensation as an important processing method can effectively improve the resolution and fidelity of seismic data. Based on sparse reflectivity model and attenuated convolution function, inversion-based compensation approaches show better stability and accuracy over traditional direct compensation schemes. However, conventional inversion-based compensation methods are conducted on single trace, which ignore the subsurface spatial continuity and make the compensated result contaminated with high-frequency noise. In this paper, we develop a structurally constrained multichannel L1-2 minimization for seismic attenuation compensation. We first estimate structure tensors from migrated seismic images. The structure tensors can be decomposed by eigenvalues and eigenvectors, which can reflect the structural orientations. Then, we introduce the estimated orientations as a regularization term to the L1-2 inversion-based compensation objective function. In this way, we can improve the stability of the compensation result and enhance the spatial continuity of the compensated seismic reflectors. The structure-guided L1-2 regularized compensation objective function can be efficiently solved via difference of convex algorithm and alternating direction method of multipliers. Synthetic and field data examples demonstrate that the proposed method possesses superior performance over conventional L1-2 regularized inversion-based compensation.