Conventional Vector Research Articles

A Double-PLLs-Based Impedance Reshaping Method for Extending Stability Range of Grid-Following Inverter Under Weak Grid

Conventional vector current control scheme has been widely used in grid-connected inverter systems. However, it suffers from severe power limitation issues under weak grids. This article reveals that the coupling effect between the power delivery and the voltage at the point of common coupling causes the static power limit, which only depends on physical parameters of the system. When the stability of the control scheme is considered, negative resistance characteristics of the phase-locked loop (PLL) mainly result in the small-signal stability limit, which is called the dynamic power limit in this article. Because the small-signal stability limit can be improved by using different control methods, it attracts lots of research attention. In this article, a simplified <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> – <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> small-signal impedance model is introduced to show the destabilizing factors. Then, an initial small-signal impedance reshaping method is proposed to counteract the major destabilizing factor caused by the PLL. Based on the initial impedance reshaping method, an improved control scheme is proposed. Through exhaustive mathematical analysis, it is proved that the dynamic power limit can be extended almost to the static power limit by using this proposed method. Finally, simulation and experimental results verify the effectiveness of the proposed method.

Adenovirus Vector With ADP Gene Induces Cytopathic Effects in HEK293 Cells Without Significant Elevation of Virus Titers.

Efficient production of adenovirus vectors is crucial for their clinical use. Adenovirus death protein (ADP), which is encoded in the E3 region of the adenovirus genome, is involved in host-cell lysis and the subsequent release of progeny virus; however, the ADP gene is often removed from the adenovirus vector genome. We have developed adenovirus vectors that possess the ADP gene and maintain a relatively large insertion capacity for foreign genes by deleting the partial E3 region. Adenovirus vector-mediated transgene expression levels and virus titers were examined. The adenovirus vectors maintaining the ADP gene showed cytopathic effect earlier than conventional adenovirus vector without the ADP gene following treatment of HEK293 cells, although there were no significant differences in total virus titers. The adenovirus vectors possessing the ADP gene showed efficient spread of progeny virus infection following transduction in HEK293 cells.

Compressive Strength Prediction of High-Strength Concrete Using Long Short-Term Memory and Machine Learning Algorithms

Compressive strength is an important mechanical property of high-strength concrete (HSC), but testing methods are usually uneconomical, time-consuming, and labor-intensive. To this end, in this paper, a long short-term memory (LSTM) model was proposed to predict the HSC compressive strength using 324 data sets with five input independent variables, namely water, cement, fine aggregate, coarse aggregate, and superplasticizer. The prediction results were compared with those of the conventional support vector regression (SVR) model using four metrics, root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and correlation coefficient (R2). The results showed that the prediction accuracy and reliability of LSTM were higher with R2 = 0.997, RMSE = 0.508, MAE = 0.08, and MAPE = 0.653 compared to the evaluation metrics R2 = 0.973, RMSE = 1.595, MAE = 0.312, MAPE = 2.469 of the SVR model. The LSTM model is recommended for the pre-estimation of HSC compressive strength under a given mix ratio before the laboratory compression test. Additionally, the Shapley additive explanations (SHAP)-based approach was performed to analyze the relative importance and contribution of the input variables to the output compressive strength.

A synthetic monopole source of Kalb-Ramond field in diamond.

Magnetic monopoles play a central role in areas of physics that range from electromagnetism to topological matter. String theory promotes conventional vector gauge fields of electrodynamics to tensor gauge fields and predicts the existence of more exotic tensor monopoles. Here, we report the synthesis of a tensor monopole in a four-dimensional parameter space defined by the spin degrees of freedom of a single solid-state defect in diamond. Using two complementary methods, we characterized the tensor monopole by measuring its quantized topological charge and its emanating Kalb-Ramond field. By introducing a fictitious external field that breaks chiral symmetry, we further observed an intriguing spectral transition, characterized by spectral rings protected by mirror symmetries. Our work demonstrates the possibility of emulating exotic topological structures inspired by string theory.

Dataset for classification of computer graphic images and photographic images

&lt;span lang="EN-US"&gt;The recent advancements in computer graphics (CG) image rendering techniques have made it easy for the content creators to produce high quality computer graphics similar to photographic images (PG) confounding the most naïve users. Such images used with negative intent, cause serious problems to the society. In such cases, proving the authenticity of an image is a big challenge in digital image forensics due to high photo-realism of CG images. Existing datasets used to assess the performance of classification models are lacking with: (i) larger dataset size, (ii) diversified image contents, and (iii) images generated with the recent digital image rendering techniques. To fill this gap, we created two new datasets, namely, ‘JSSSTU CG and PG image dataset’ and ‘JSSSTU PRCG image dataset’. Further, the complexity of the new datasets and benchmark datasets are evaluated using handcrafted texture feature descriptors such as gray level co-occurrence matrix, local binary pattern and VGG variants (VGG16 and VGG19) which are pre-trained convolutional neural network (CNN) models. Experimental results showed that the CNN-based pre-trained techniques outperformed the conventional support vector machine (SVM)-based classifier in terms of classification accuracy. Proposed datasets have attained a low f-score when compared to existing datasets indicating they are very challenging.&lt;/span&gt;

Performance Analysis and Experimental Validation of 240°-Clamped Space Vector PWM to Minimize Common Mode Voltage and Leakage Current in EV/HEV Traction Drives

High switching frequency inverters in hybrid electric vehicle/electric vehicle (HEV/EV) drivetrains present problems such as common mode voltage (CMV) and leakage current that have negative impacts on the performance of the drivetrain. Various reduced CMV PWM (RCMV-PWM) methods have been introduced in the literature that reduces the CMV but typically at the expense of increased total harmonic distortion (THD) and switching loss simultaneously. In this article, a low-loss PWM method called 240°-clamped space vector PWM (240CPWM) is discussed in terms of its CMV and leakage current characteristics. It is analytically shown that 240CPWM reduces the peak CMV and the number of CMV pulses in a switching period by 66.7% each, and RMS CMV by 21%, while simultaneously reducing the switching loss by 85%, and achieving similar THD at maximum speed (and lower THD at other speeds) as compared to conventional space vector PWM (CSVPWM). Detailed analysis of CMV and leakage current is presented for 240CPWM and compared with CSVPWM and discontinuous PWM (DPWM1) with constant and variable dc-link voltage control. Experimental results from a 10-kW hardware prototype are presented that conform to the analytical discussions and validate the superior performance of 240CPWM.

At-line quality assurance of deep-fried instant noodles using pilot scale visible-NIR spectroscopy combined with deep-learning algorithms

Deep-fried instant noodles produced in a pilot scale facility were monitored for quality parameters using at-line visible-NIR spectroscopy (380–1650 nm) combined with deep-learning algorithms. To build robust calibrations, a wider range of quality parameters for instant noodles viz., moisture (1.6–11.04%), crude protein (8.34–14.39%), total fat (12.38–26.68%), and total ash (1.18–3.15%) were selected. The original raw spectral data was subjected to different pretreatments (standard normal variate (SNV), detrending (DT), first derivative (FD), multiplicative scattering correction (MSC), among others) before being optimized for wavelength selection feature algorithm by competitive adaptive reweighed sampling (CARS). The calibration models were established using deep-learning algorithms based on conventional partial least squares regression (PLSR) and support vector machine regression (SVMR). In general, the SVMR modeling gave an optimum prediction statistics (pretreatment method, coefficient of determination ( R 2 ), root mean square error of prediction (RMSEP), ratio of prediction to deviation (RPD)) for moisture (CARS–SNV–DT, 0.98, 0.32, 6.7), crude protein (CARS–FD, 0.98, 0.18, 8.15), and total fat (CARS–MSC, 0.99, 0.39, 10.15) whereas partial least squares regression (PLSR) gave for total ash (CARS–raw, 0.94, 0.12, 4.34). In particularly for noodle manufacturers, the unification of visible-NIR spectroscopy and deep-learning algorithm is a promising to realize sustainability in quality assurance and control. • Vis-NIR and deep-learning algorithm applied to quality monitoring of noodles. • Calibration models were optimized by CARS feature selection algorithm. • CARS-SVMR gave best predictions for moisture, crude protein, and total fat. • SVMR algorithm successfully used for at-line vis-NIR based quality monitoring.

Design and analysis of monolithic integrated MEMS vector hydrophone micro-array

Based on the high sensitivity and miniaturization advantages of MEMS vector hydrophone, we proposed and designed a monolithic integrated micro-array vector hydrophone composed of multiple sensor units. The theoretical model shows that the micro-array can improve the structural sensitivity and output signal-to-noise ratio while eliminating the problem of port and starboard ambiguity. Meanwhile, the micro-array structure clearly reduces the installation error of conventional vector array and improve the directional accuracy. Taking 5-element micro-array as an example, the resonance frequency in wet mode reaches 956 Hz that meets the requirement of test frequency band. Through theoretical and computational analysis, the sensitivity of micro-array is increased 14 dB and the SNR is increased 3.1 dB compared with that of the single vector hydrophone. The standing-wave tube experiment verified the directional effect of vector micro-array. The research of vector hydrophone micro-array is helpful to the application of underwater acoustic engineering.

A coordinated and steadily fault ride through strategy under short-circuit fault of the wind power grid connected system based on the grid-forming control

With the continuous improvement of the penetration level of wind power in the power system, the grid-forming mode of wind turbine will gradually become one of the main modes of system synchronization. The power electronic equipment based on grid-forming control has the ability of frequency dynamic regulation, reactive power voltage regulation, weak current network operation stability and island operation similar to the conventional synchronous generator, however, the problem of strong electromagnetic stress faced by power electronic equipment under grid-forming control will be the key factor restricting the wide application and promotion of grid-forming technology. In particular, the fault ride through problem of the wind turbine under the grid-forming control will face more severe challenges. This paper is based on a switched fault ride through strategy, that is, in case of power grid fault, it is quickly converted from grid-forming control under normal working conditions to the conventional current vector control, so as to facilitate fault current limiting and realize fast dynamic reactive power support. In this paper, a fault ride through optimization control strategy of grid-forming wind turbine is proposed. During the fault, the threshold setting of entering/ exiting the fault ride through control is optimized to form hysteresis control, so as to improve the switching misoperation of control strategy caused by the large fluctuation of grid voltage in the process of fault. Finally, simulation results show that the earlier switching back to the grid-forming control is not the more conducive to the stability of the system, and there is an optimal switching time. The results verify the proposed strategy can effectively improve the transient stability of power system with grid-forming mode of the wind turbine.

A novel multiport converter switching scheme to integrate multiple renewable energy sources

SummaryIn this paper, an innovative switching scheme named simultaneous space vector modulation (SSVM) is proposed for integrating various AC sources in the energy industry using a unified multiport converter. The proposed SSVM technique is applied to the multileg topology of a multiport converter, which is an encouraging option for the grid integration of renewable energy sources and multimachine drives. Considering the shared leg in the multileg converter, the proposed SSVM can utilize the utmost simultaneous switching states between different ports, resulting in lower switching loss and better DC‐link voltage utilization compared with the conventional sequential space vector modulation approach. A novel decision matrix concept is introduced to identify the simultaneous switching states. For this aim, according to the number of ports of the multileg converter, decision matrices containing valid simultaneous switching states are first calculated. Then, they are defined as look‐up tables in the proposed SSVM to be retrieved and exploited in every sampling period. The effectiveness of the proposed SSVM for a seven‐leg version of the multileg converter is assessed using the simulation analysis and real‐time validation. The capability of the proposed SSVM‐based multiport converter in grid integration of AC renewable energy sources is also verified considering two permanent magnet synchronous generator (PMSG)‐based wind turbines with real wind speed patterns. The simulation results confirm that the proposed SSVM is properly able to manage the power flow between different ports and improve the DC voltage utilization and switching loss compared with the sequential SVM.

An Optimized Asymmetric Pulsewidth Modulation for Sensorless Control of Permanent Magnet Synchronous Machines

This article proposes an optimized asymmetric pulsewidth modulation (OAPWM) for saliency-based sensorless control of permanent magnet synchronous machines (PMSMs). Compared with the conventional symmetric space vector PWM, OAPWM has merits of longer active vectors and more accurate current slope measurements, which are beneficial to the low-speed sensorless drives. In OAPWM, a distributed zero vector is inserted between two adjacent active vectors. Thus, the current ripple and the power loss can be reduced. Moreover, the length of zero vector is optimized considering the current ripple and modulation index. Then, a current oversampling method and the least square algorithm are adopted to improve the calculation accuracy of the current slope. And the average phase current in one PWM period is calculated using six sampling points. The effectiveness of OAPWM for sensorless control is verified on both 500- and 1500-W PMSMs based on a single field programmable gate array. In comparison with the conventional methods, more accurate position estimation can be achieved during both the transient and steady-state processes.

Design of an array of piezoresistive airflow sensors based on pressure loading mode for simultaneous detection of airflow velocity and direction.

As an irreplaceable element for obtaining airflow information in many engineering scenarios, airflow sensors have gained increasing attention across the fields of aerospace engineering, environmental engineering, sustainable energy exploitation, meteorology research, and so on. As one of the mainstream airflow sensing principles, piezoresistive airflow velocity sensors have experienced rapid growth over the years, while effective vector airflow sensors with the ability of detecting both airflow velocity and direction based on the piezoresistive principle are scarce. Here, on the basis of our developed piezoresistive airflow velocity sensors based on pressure loading mode, we design an array of these sensors and propose a corresponding explicit algorithm for simultaneous detection of airflow velocity and direction. This sensor array configuration enables an automatic recognition function of the quadrant of incoming airflow, which can significantly simplify the reverse calculation of airflow information compared with conventional vector airflow sensors. The experimental results demonstrate the decent performance of this sensor array for identifying both airflow velocity and direction. This study not only fills the gap between our developed airflow velocity sensor and the ability of detecting airflow direction but also presents a simple and universal array-based strategy for vector airflow sensing, which could be widely applied in airflow sensors based on other principles.

Single nucleotide polymorphism (SNP) in the doublesex (dsx) gene splice sites and relevance for its alternative splicing in the malaria vector Anopheles gambiae

Background: The malaria burden continues to be significant in tropical regions, and conventional vector control methods are faced with challenges such as insecticide resistance. To overcome these challenges, additional vector control interventions are vital and include modern genetic approaches as well as classical methods like the sterile insect technique (SIT). In the major human malaria vector Anopheles gambiae, a candidate gene favourable for sterility induction is the doublesex (dsx) gene, encoding somatic sexually dimorphic traits in mosquitoes. However, the mechanism that regulates the expression of this gene in anopheline mosquitoes is poorly understood. This study aimed to screen the An. gambiae dsx gene splice site sequences for single nucleotide polymorphisms (SNPs) that could be critical to its alternative splicing. Methods: Variant annotation data from Ag1000G project phase 2 was analysed, in order to identify splice-relevant SNPs within acceptor and donor splice sites of the An. gambiae dsx gene (Agdsx). Results: SNPs were found in both donor and acceptor sites of the Agdsx. No splice-relevant SNPs were identified in the female-specific intron 4 acceptor site and the corresponding region in males. Two SNPs (rs48712947, rs48712962) were found in the female-specific donor site of exon 5. They were not specific to either males or females as the rs48712947 was found in female mosquitoes from Cameroon, and in both males and females from Burkina Faso. In the other splice sites, the intron 3 acceptor site carried the greatest abundance of SNPs. Conclusions: There were no gender association between the identified SNPs and the random distribution of these SNPs in mosquito populations. The SNPs in Agdsx splice sites are not critical for the alternative splicing. Other molecular mechanisms should be considered and investigated.

A self-assembly reproducible nanoplatform enables cancer phenotypic lethality in solid tumors

Cancer phenotypic lethality targets a nonessential enzyme in normal cells that is required for cancer survival, which can overcome the problem of the high degree of intra-tumor heterogeneity and be more widely applicable, irrespective of the cancer genotype. Altered redox regulation is a cancer phenotype and damages both the DNA and free deoxynucleoside triphosphates (dNTPs) pool. MutT Homolog1 (MTH1) plays a critical role in removing oxidized dNTPs, avoiding incorporation of these damaged bases. This study aimed to construct a self-assembly reproducible nanoplatform (SRNA) to actualize cancer phenotypic lethality in solid tumors by efficiently delivering of MTH1 siRNA (siMTH1). Compared with conventional polymer vectors, the synthesized cholesteryl-peptides had precise molecular weights, good biocompatibility and low variability. Thus, the cholesteryl-peptides were used to form a compact SRNA with siMTH1 and protect siMTH1 against degradation. The SRNA silenced MTH1 expression and accumulated oxidized dNTPs in cancer cells, leading to a therapeutic response in ovarian cancer. In summary, the SRNA for the efficient delivery of siMTH1 may provide a practical paradigm to induce cancer phenotypic lethality in solid tumors.

Analysis and experimental demonstration of propagation features of radially polarized specific non-uniformly correlated beams.

With the development of the unified theory of coherence and polarization, the novel physical properties generated by different correlation structures of vector partially coherent beams (PCBs) have attracted much attention. Recently, a new class of structured beams have been proposed [Opt. Lett.45, 3824 (2020)10.1364/OL.397316], called vector specific non-uniformly correlated beams. These beams combine non-uniform polarization and non-uniform correlation, and they exhibit propagation features not seen in conventional vector PCBs. In this Letter, we continue the analysis of the previous work, taking radially polarized Hermite non-uniformly correlated (RPHNUC) beams as an example, and focus on the physical interpretation of the peculiar propagation features of such beams. We verify the predicted behavior of RPHNUC beams through experiment.

Combined Vector and Direct Controls Based on Five-Level Inverter for High Performance of IM Drive

The goal of this study was to figure out how to regulate an induction motor in a hybrid electric vehicle. Conventional combined vector and direct control induction motors take advantage of the advantages of vector control and direct torque control. It is also a method that avoids some of the difficulties in implementing both of the two control methods. However, for this method of control, the statoric current has a great wealth of harmonic components which, unfortunately, results in a strong undulation of the torque regardless of the region speed. To solve this problem, a five-level neutral point clamped inverter was used. Through multilevel inverter operation, the voltage is closer to the sine wave. The speed and torque are then successfully controlled with a lower level of ripple in the torque response which improves system performance. The analysis of this study was verified with simulation in the MATLAB/Simulink interface. The simulation results demonstrate the high performance of this control strategy.

Spherically polarized vector Bessel vortex beams

A different type of Bessel-like vortex beams with their intensity spherically modified by a singular polarization structure is introduced. Conventional vector Bessel-Gaussian beams are either linearly or radially (and azimuthally) polarized and their transverse structure is preserved under propagation. In this work, the Bessel-like beams with a Gaussian envelope are spherically polarized: the electric fields are oriented along the radius vector or along with a combination of meridional and azimuthal vectors. For the implementation of such beams, we investigate their vector spatial spectra. The intensity distribution of the beam can be controlled by a proper choice of parameters such as the cone angles of individual plane-wave components and sizes of Gaussian apertures. In the two limiting cases of axicon angles, spherically polarized Bessel beams form either two optical needles or optical-bottle-like intensity patterns.

Exploiting Signal Linear Trend in the Time Domain to Enhance Speech Feature

Speech feature extraction usually begins with transforming the signal from the time domain to the frequency domain via integral transforms. Human speech contains sine-shape waves and a linear trend in the time domain, usually ignored. This research proposes two new methods to strengthen the speech feature vector using this unused factor. Before transforming the speech frames into the frequency domain, we use linear regression to identify each speech frame’s linear trend or linear envelope in the time domain. Then we remove the impact of that trend to normalize the signal and emphasize the stationary elements in the signal. The proposed feature vector includes parameters from the linear envelope and the conventional vectors as a spectrum or MFCC. Experimental results demonstrate that the impact of the linear envelope is significant and the linear envelope subtraction is a meaningful stage. Our new features emphasize the stationary property in the speech signal and improve the result for speech recognition in terms of error rate.

A modified type-2 neuro-fuzzy SVM-based inverter fed IM drive

In indirect vector control, the conventional speed and current controllers operate satisfactorily when the operating point is constant. But the operating point is always dynamic; the reference voltages obtained in a closed-loop system feeding to the inverter contains more harmonics. Due to this, the pulses which are going to produce are uneven and in turn, understudy creates the inverter output voltages produced with more harmonics. In order to produce a better output voltage from the inverter, this paper presents the neuro-fuzzy type-2 (NFT2) space vector modulation technique. Performance comparison of the inverter is done with conventional space vector modulation (SVM) and neuro-fuzzy type-1 (NFT1) system using MATLAB simulation and experimental validation. The performance parameters of the induction motor based on current, torque, and speed with neuro-fuzzy type-2 space vector modulation is compared with conventional and type-1 neuro-fuzzy SVM. The % THD of inverter output voltages are also compared. The experimental validation of a DSpace-1104 is used to analyse the performance of the induction motor which is obtained by the simulation. The experimental validations are carried out considering 2HP induction motor in the lab.

Implementation of Integer Factor based Space Vector PWM through Digital approach for Grid Connected Multilevel Inverters

Space vector pulse width modulation control for grid connected multilevel inverters are very popular. However, it gets exceedingly tough with the increase in the number of output voltage levels. The total number of possible switching states will increase with the output voltage level of the inverter. Due to increase in the number of switching states, the sub triangles in the various sectors of the hexagon will also increase, that result in increased complexity and storage requirements for implementation using conventional space vector methods. The objective of the paper is to simplify and generalize the space vector algorithm for an n-level inverter. The proposed algorithm uses integer factor approach to find the exact location of the reference vector, synthesize switching times and generate the nearby switching states. It is a generalized algorithm applicable to any sequence and can be applied to any level judiciously. In this article description of the algorithm is given for a three–level inverter and validated by implementing experimentally using dspace control desk. The PWM signals generated by three level Space Vector algorithm with conventional switching sequence of 0127 is used to control an open end winding induction motor fed with two two-level inverters. The performance factor of motor voltage and line current THD at different modulation index is measured and compared with simulation result.