Elimination Of Distortion Research Articles

A Modulation Method With Current Zero-Crossing Distortion Elimination and Voltage Balance Control for the RSHMC Converter

A Modulation Method With Current Zero-Crossing Distortion Elimination and Voltage Balance Control for the RSHMC Converter

A hybrid carrier‐based discontinuous PWM with neutral‐point voltage ripple and current distortion reduction for Vienna rectifier

AbstractThe three‐level Vienna rectifier is widely used in industrial applications, such as electric vehicle charging systems and telecommunication power systems. Discontinuous pulse width modulation (DPWM) is widely used in three‐level AC/DC converters due to its features of switching loss minimization. However, the problems of neutral‐point voltage ripple, current zero‐crossing distortion, and switching losses are mutually coupled for the Vienna rectifier. To address these issues, a hybrid carrier‐based discontinuous pulse width modulation (HCB‐DPWM) with reduced neutral‐point (NP) voltage ripple and current distortion is proposed. First, the /6 clamping period of the conventional DPWM is divided into three‐type clamping intervals, which reduce NP voltage ripple with shortened clamping period. Then, the elimination of current distortion around the current zero‐crossing point and the switching loss reduction are investigated. The implementation of the proposed HCB‐DPWM is given in detail. Finally, the simulation and experimental results of the Vienna rectifier are presented to validate the performance that the proposed HCB‐DPWM can eliminate current zero‐crossing distortion and reduce neutral‐point voltage ripple with different modulation indices.

Experimental and numerical research for the failure behavior of the dieless clinching joints

In this work, the failure behavior of dieless clinching joints for AA5052-H32 aluminum alloy under cross tension and tensile shear loading conditions was investigated by experimental and simulation methods. Firstly, The VUMAT subroutine for the N–H shear-modified GTN model (Proposed by Nahshon and Hutchinson, a modified GTN model considering hole shear effects) was written. Subsequently, the conventional and shear parameters calibration was accomplished. A finite element model (FEM) for the failure process of dieless clinching joints based on the N–H shear-modified GTN microscopic damage model, elimination of large deformation mesh distortion and consideration of the material hardening history was established. In addition, the deformation, damage and destruction processes of the joint under two loading conditions were analyzed. And macro/microfracture analysis of the failed joints was performed to further reveal the failure behavior. The results show that the established FEM of the failure process agrees well with the experimental results and failure modes are consistent. The model accuracy in predicting the tensile and shear loads is 91.9% and 92.7%, respectively. This provides a reference for the process design and joint arrangement of the dieless clinching joints in practical applications.

A Novel Compliant Connection Mechanism with Thermal Distortion Self-Elimination Function.

As a novel technology for fabricating large-screen OLED devices, OLED inkjet printing places extreme demands on the positioning accuracy of inkjet printing platforms. However, thermal deformation of the connection mechanism often reduces the printing precision of OLED printing equipment, significantly impacting overall print quality. This study introduces a compliant connection mechanism that achieves precise positioning of the inkjet printing platform and can self-eliminate thermal distortion. The design of the mechanism's core component is based on the Freedom and Constraint Topology (FACT) principle. This component is constructed from three distinct compliant sections arranged in series, collectively providing three degrees of freedom. Furthermore, the resistance to deformation caused by gravity and other external forces was evaluated by analyzing both vertical and horizontal stiffness. To validate the mechanism's thermal distortion elimination and gravity resistance capabilities, finite element analysis (FEA) was carried out. The results demonstrate that the mechanism effectively reduces the maximum deformation of the platform by approximately 46% and the average deformation across the entire platform by approximately 59%. These findings confirm that the mechanism has potential in high-precision positioning tasks that need to mitigate thermal distortion.

Elimination of distortions of weak images of astronomical objects on the example of Saturn, Jupiter and their satellites

Elimination of distortions of weak images of astronomical objects on the example of Saturn, Jupiter and their satellites

The important of eliminating energy market distortions: The perspective of industrial green productivity

The elimination of energy market distortions (EMDs) is a key objective of energy marketization reform and plays a crucial role in advancing green industrial development. This study, based on the provincial panel data from 2008 to 2018 in China, first measured the EMDs from the perspective of competition and non-competition distortions, and then investigated the effect and mechanism of EMDs on industrial green total factor productivity (GTFP). The results indicate a declining trend in EMDs from 2008 to 2018, with a hierarchical distribution from high to low across the western, central, and eastern regions. Particularly, competitive distortions of EMDs inhibit industrial GTFP by negatively affecting green technological innovation. Moreover, the inhibitory effect is more pronounced in the eastern region. Additionally, the inhibitory effect amplifies as local governments face increasing pressures related to economic growth and fiscal demands.

Ortho-NeRF: generating a true digital orthophoto map using the neural radiance field from unmanned aerial vehicle images

ABSTRACT True Digital Orthophoto Maps (TDOMs) have high geometric accuracy and rich image characteristics, making them essential geographic data for national economic and social development. Complex terrain and artificial structures, automatic distortion elimination and occluded area recovery in TDOM generation pose significant challenges. Hence, the need for further improvements in both mapping accuracy and automation is highlighted. In this paper, we present an approach for generating a TDOM based on a Neural Radiance Field (NeRF) without utilizing prior three-dimensional geometry information called an Ortho Neural Radiance Field (Ortho-NeRF). The Ortho-NeRF divides a large-scale scene into small tiles, implicitly reconstructing each tile by selecting pixels on posed images, and individually generate TDOMs of all tiles using a true-ortho-volume rendering before mosaicking. Additionally, the Ortho-NeRF uses a strategy to skip empty spaces and adaptively set the spatial resolution of a voxel grid, improving the generated TDOM quality with fewer computational resources. Many experiments showed that our approach outperforms ContextCapture, Metashape, Pix4DMapper, and Map2DFusion, especially in challenging areas. Owing to its global consistency and continuous nature, Ortho-NeRF was able to effectively reconstruct the geometry information and details, generating TDOMs without distortion or misalignment. Eight ground control points were randomly selected to evaluate the geometric accuracy of the TDOMs, with an average median error of 0.267 m. The length between two points on a plane was also measured for quantitative evaluation, with a mean absolute error of 0.08 m and a mean relative error of 0.14%. Compared with the NeRF efficiency, that of the Ortho-NeRF increased 104 times in training and about 1000 times in rendering.

Metrology of Short-Length Measurers-Development of a Comparator for the Calibration of Measurers Based on Image Processing and Interferometric Measurements.

For the calibration of linear scales, comparators are generally used. Comparators are devices that enable the movement of an evaluation apparatus over a calibrated scale along a linear base with high precision. The construction of a comparator includes a movable carriage that carries the device for the evaluation of the position of the given edge of the line scale relative to the beginning of the scale. In principle, it involves a camera capturing the scale of the measurer, where the position of the camera's projection center is measured using an interferometer. This article addresses the development of a comparator assembled from low-cost components, as well as the description of systematic influences related to the movement of individual parts of the system, such as the inclination and rotation of the camera and directional and height deviations during the carriage's movement. This article also includes an evaluation of the edge of the given scale with subpixel accuracy, addressing distortion elimination and excluding the influences of impurities or imperfections on the scale. The proposed solution was applied to linear-scale measurers, such as leveling rods with coded and conventional scales and measuring tapes. The entire process of measurement and evaluation was automated.

Optical properties of Sn-substituted GeTe phase-change materials under high pressure

The emerging phase change materials (PCMs) have attracted much attention due to their unique properties and applications. However, the optical properties of PCM at high pressures have not been well explored. In this work, the microstructure and optical properties of GeTe and Sn-substituted GeTe at high pressures up to 30 GPa have been systematically investigated. We find that the substitution of small amounts of Sn for Ge combined with the introduction of high pressure can induce an optical contrast of 117% in crystalline GeTe, which is even higher than the highest optical contrast reported so far (90%) caused by amorphous GeTe to crystalline GeTe. The pressure-induced contrast does not originate from any phase transition as previously, but from the combined effect of Peierls distortion elimination and Ge vacancy formation, which leads to an increase in carrier concentration. The relationship between pressure/atomic composition, Peierls distortion/vacancy formation, and optical contrast can be well explained by a combination of experiments and theoretical calculations. Therefore, this study reveals the effect of high pressure on the optical properties of PCMs and provides new ideas for the design of high-optical-contrast PCMs.

Damage To Brick-Walled Buildings And Effective Ways To Strengthen Brick Structures When Baratarafing Them

This article examines the causes of defects in brick walls, research into the actual operation of structural elements, and improvement of methods for the reliable elimination of cracks, deformations, damage and distortions that arise when assessing their technical condition

Cooperative correction method for distortion and dispersion of deflected field of view in Risley-prism bionic-human-eye imaging systems.

The Risley-prism imaging system (RPIS) is a powerful way to achieve bionic human eye imaging with great advantages on large field of view (FOV) and variable resolution imaging owing to the autonomous controlled deflection of light. But the imaging dispersion originating from nonlinear and uneven light deflection results in limited imaging wavelength that seriously hinders its application. The existing solutions for imaging dispersion mainly rely on the hardware, which generally has bulky structure and limited improvement on image. Besides, the existing image evaluation methods for dispersion are not suitable for RPIS due to inhomogeneous dispersion. Herein, this paper systematically analyzes the mechanism and characteristics of dispersion in the RPIS, and proposes a cooperative correction method for image distortion and dispersion of multiple-color imaging, achieving the elimination of distortion and dispersion simultaneously without changing the optical structure. A dispersion evaluation index based on Pearson's correlation coefficient (PCC) is also established, and the objectivity and validity of the index are proved by experiments. Furthermore, a kind of compact RPIS based on an RGB camera is built, and both indoor and outdoor experiments are conducted. The experimental results demonstrate that proposed algorithm has strong universality and robustness for various scenes and targets.

Distortion elimination for serpentine duct at various Mach numbers using co-flow jet active flow control

This paper numerically investigates Co-flow Jet (CFJ) active flow control (AFC) for eliminating the AGARD M2129 serpentine inlet distortion with throat Mach number (Mth) varying from 0.42 to 0.79. The configuration was optimized at design Mth of 0.79 in a prior study. The current objective is to investigate the CFJ S-duct performance at off-design Mth with the fixed geometry. The high-order FASIP in-house code is used to conduct 3D Reynolds Averaged Navier-Stokes (RANS) simulation with the one-equation Spalart-Allmaras (S-A) turbulence model. The CFD simulation is well validated with the experiment of AGARD test cases in the studied Mach numbers. Results show that CFJ virtually eliminates the flow distortion for all the studied Mth. However, the off design Mth have lower energy efficiency. At the design Mth, CFJ requires the lowest power coefficient (Pc) to eliminate the flow separation and distortion. The exergy analysis indicates that CFJ S-duct at the design Mth has the highest system energy efficiency with the EIPR (ratio of exergy increase to the power required) exceeding 1. At the off-design Mth, EIPR is lower than 1 because the shifts of separation-onset spot and adverse-pressure-gradient region make CFJ injection and suction no longer at the most efficient location. This leads to the rising of the CFJ power coefficient even though the actual power is less. Nevertheless, the overall system is still very efficient at off-design Mth for the CFJ S-duct with the CFJ energy expenditure recovered by 72%, 90%, 96% for Mth of 0.42, 0.55, and 0.69, respectively.

Optimization of Butt-joint laser welding parameters for elimination of angular distortion using High-fidelity simulations and Machine learning

The high temperature gradient and high cooling rate induced in the butt-joint laser welding process generate a high residual stress, which can result in significant distortion of the final weld. Previous researches usually employed experimental approach to search for optimal parameters which is costly and time consuming. Additionally, there was several studies that used simulation to compute the distortion and to find optimal parameters, however, these studies neglect the effect of solid cooling rate and size of the heat-affected zone (HAZ) in the process of finding optimal parameters. Accordingly, the present study proposes a new systematic framework based on finite element (FE) simulations, regression analysis, and two artificial neural networks (ANNs) for determining the laser welding parameters (i.e., the laser power and welding speed) which minimize the angular distortion of the laser-welded butt joint and enhance the mechanical properties. In the proposed approach, to determine the variables of the selected double-conical heat source model for any combination of the laser power and welding speed is studied within the feasible design space. The variables are then imported into a three-dimensional COMSOL Multiphysics FE model to predict the melt pool dimensions, solid cooling rate, and size of the HAZ as a function of the laser power and welding speed. Finally, the processing map produced by the ANN is screened by four quality criteria based on the melt pool depth, angular distortion, cooling rate, and HAZ width, respectively, to determine the optimal laser welding parameters which minimize the angular distortion and maximize the mechanical properties. It shows that SS316L tensile test specimens fabricated using the optimal parameters have a tensile strength (662 MPa) which is higher than that of the base metal (660 MPa). Furthermore, the angular distortion of the butt-joint samples is less than 564 µm. Thus, the effectiveness of the proposed optimization procedure is confirmed.

Parametric Doppler correction for wayside array acoustic signal via short-time reconstruction

The trackside acoustic detection system (TADS) plays a vital role in vehicle bearings condition monitoring. However, the inevitable Doppler distortion embedded in collected data will bring considerable difficulties to defect inspection and diagnosis in the system. The distortion elimination approaches mainly achieve spectrum recovery based on time-domain interpolation resampling (TIR) in a data-driven way. These will be further limited by the requirement to signal to noise ratio (SNR) or calculation speed. Considering the principle of wayside acoustic physical model and the benefits of array acoustic in practice, this study proposes an adaptive parametric Doppler correction (PDC) scheme based on short-time reconstruction (STR), including perception modeling, inverse perception optimization and Doppler correction. Firstly, mathematical modeling with multiple perception operators, including acoustic amplitude modulation operator, frequency modulation operator and array time delay operator, a wayside acoustic physical model based on array sensing is established. Secondly, through the corresponding inverse multiple perception operators, a transition signal with frequency-domain energy concentrated is obtained for the optimal moving parameters searching. Thirdly, within short-time sequence segments of the sound source, the real-time position recovery is realized via the proposed STR with formulaic propagation delay compensation. Theoretically, it can be seen that the proposed PDC scheme can simultaneously recover the amplitude, frequency distribution and phase of the Doppler signal, which can be applicable to all wayside acoustic diagnosis scenarios. With the correction analysis of simulation and experimental array defect signals, it can be confirmed that the proposed STR-based PDC scheme is effective for Doppler signal recovery in high fidelity, and has great potential to the real-time diagnosis of TADS.

Distortion-Elimination Hybrid OFDM With Low Complexity for Optical Wireless Communications

In optical wireless communications (OWC), hybrid optical orthogonal frequency division multiplexing (O-OFDM) schemes, such as hybrid asymmetrically clipped O-OFDM (HACO-OFDM) and layered asymmetrically clipped O-OFDM (LACO-OFDM), enjoy both high power and spectral efficiency. However, due to the non-orthogonal transmission of signal components induced by the clipping distortion, successive interference cancellation (SIC) is required in these hybrid O-OFDM schemes, leading to notably increased complexity. In this paper, we conceive novel hybrid O-OFDM schemes to offer both high spectral and power efficiency, whilst possessing low complexity. By elaborately designing a time-domain (TD) distortion elimination methodology at the transmitter, a novel distortion-elimination hybrid O-OFDM (DEHO-OFDM) is first proposed, which combines asymmetrically clipped O-OFDM (ACO-OFDM) and pulse-amplitude-modulated discrete multitone (PAM-DMT) in an interference-free manner. In order to further improve the spectral efficiency, an enhance DEHO-OFDM (EDEHO-OFDM) is designed by activating the remaining subcarrier resources. Both DEHO-OFDM and EDEHO-OFDM can be realized through a single-IFFT transmitter and standard OFDM receiver, leading to much lower complexity than the existing hybrid O-OFDM schemes. Simulation results have demonstrated the superiorities of the proposed schemes over HACO-OFDM and LACO-OFDM in terms of peak-to-average-power ratio (PAPR) and bit error rate (BER).

Value analysis with blockchain-based information transparency system to eliminate information distortion

Information distortion is common in supply chains, especially demand information distortion. An easily-thought way of eliminating information distortion is information sharing. Although there exist many information sharing mechanisms that can coordinate the supply chains, they are not easy to implement due to their rigid implementation conditions. Consequently, many upstream manufacturers in reality commonly buy data from downstream retailers to eliminate demand information distortion, or may build a blockchain-based information transparency system (BITS), which is an alternative way proposed in this paper. The main purpose of this paper is to investigate how the two alternative ways perform in eliminating demand information distortion within supply chains. In specific, we study a two-echelon supply chain consisting of one manufacturer and one retailer under three scenarios: benchmark scenario with demand distortion, demand distortion elimination through data buying and through constructing BITS. Our findings are the following (Babich and Hilary, 2020): Eliminating demand distortion by BITS can always bring the manufacturer additional value, but a higher information transparency of BITS is not always better to the manufacturer, and the manufacturer chooses a fully transparent BITS to eliminate demand distortion only when the demand distortion is relatively large (Carley and Lin, 1997); The data purchase way of eliminating demand distortion can bring additional value to the manufacturer only when the data-buying cost is not very large (Chen and Huang, 2007); As compared to the data-buying scenario to eliminate demand distortion, the BITS construction scenario can generate more additional values for the manufacturer if the demand volatility is relatively small, or when the cost coefficient of building BITS is relatively small (CachonGérard and Fisher, 2000); If the retailer bears the BITS construction cost, the retailer prefers to proactively share the BITS construction cost rather than passively bear it completely.

Crop leaves high-resolution images analysis and segmentation by a convolutional neural network under small sampling condition

The authors propose an algorithm for analysing and segmenting high-resolution images of cultivated plant leaves by a convolutional neural network of deep learning in conditions of small samples. The algorithm implemented in the hardware and software complex includes images preprocessing procedures with the elimination of distortions if they are present, data augmentation to increase the number of variations, classification of signs by textural characteristics in order to identify diseases with subsequent segmentation of images of affected leaves.

Модуль стиснення зображень на основі нейро- мережевих автокодувальників

A new approach is proposed to data compression in the form of a neural network module based on the structure of autoencoders, which has the most optimal learning time, compression level and obtains sufficiently clear image reconstruction. The main mechanisms for building the structure of encoder and decoder neural networks, which are used as a module, have been developed. The main data for the reconstruction were selected from the open data set Fashion-MNIST, which allows simplified testing of neural network structures, the process of their training and obtaining results. Approaches to image reproduction using neural network layers of convolution and inverse convolution are analyzed. An analysis of the impact on the quality of the resulting image reconstruction of the structure of the output module, which is used to compress the input image, was carried out. Atypical behavior was found during the increase of layers in the structure of the autoencoder, which did not lead to an increase in the quality of image reproduction. The basic necessity of changing the structural parts of the autoencoder and its application in combination with other technologies to obtain a better reproduction result and the elimination of distortions is highlighted.

Motion Distortion Elimination for LiDAR-Inertial Odometry Under Rapid Motion Conditions

Motion Distortion Elimination for LiDAR-Inertial Odometry Under Rapid Motion Conditions

Post-war restructuring of the agricultural sector of Ukraine: elimination of distortions to achieve stability and well-being

The relevance of the study is due to the formation of the rent-seeking model of the agricultural sector, the dominance of the raw material structure of export and the related socio-economic problems that have escalated to the scale of national security in the context of Russia’s war against Ukraine. The purpose of the research is to identify cause-and-effect relationships of structural distortions of the agricultural sector and justify the state regulatory policy aimed at strengthening its sustainability. The methods of empirical observation, expert evaluations, dynamic series of statistics, monographic, critical analysis, graphic tools, statistical database processing, system-structural processing of material, abstract-logical and other tools. The scale of destruction of assets of the agricultural sector and ecology as a result of Russian aggression was revealed. The institutional prerequisites for structural distortions in the agricultural sector are substantiated. The dynamics of export-import operations of the agricultural sector and alternative possibilities in the international division of labour to increase its efficiency are highlighted. Measures to restore animal husbandry by activating micro and small businesses, establishing equivalent relations of market counterparties and their observance of virtuous practices have been developed. The practical significance is reflected with a proposal on overcoming the protracted crisis in animal husbandry through an inclusive approach to the realization of the potential of micro, small, and medium-sized farms