基于DDS的数字脉冲电火花沉积电源研究

在电火花沉积加工中,脉冲电源的放电参数对沉积效果和加工效率有重要影响。针对传统电火花沉积电源放电参数可控性差的问题,基于直接数字频率合成(DDS)技术全数字化调制、输出稳定的特性,设计了一种数字脉冲电火花沉积电源。以单片机和DDS芯片为核心来控制斩波电路输出加工脉冲,可实现放电电压、频率等参数的较精确控制以及宽范围内的无极调节。经测试,控制及驱动模块输出信号稳定、准确且频率误差在1 Hz以内,放电电压波形可控性好,满足电火花沉积加工的要求,可用于电火花沉积加工基础研究。

基于多尺度Scale-Unet的单样本图像翻译

随着生成对抗网络(GAN)的发展,基于单样本的无监督图像到图像翻译(UI2I)取得了重大进展。然而,以前方法无法捕获图像中的复杂纹理并保留原始内容信息。为解决这个问题,提出了一种基于尺度可变U-Net结构(Scale—Unet)的新型单样本图像翻译结构SUGAN。所提出的SUGAN使用Scale—Unet作为生成器,利用多尺度结构和渐进方法不断改进网络结构,以从粗到细地学习图像特征。同时,提出了尺度像素损失scale-pixel来更好地约束保留原始内容信息,防止信息丢失。实验表明,与SinGAN、TuiGAN、TSIT、StyTR2等公共数据集Summer■Winter、Horse■Zebra上的方法相比,该方法生成图像的SIFID值平均降低了30%。所提方法可更好地保留图像内容信息,同时生成详细逼真的高质量图像。

基于改进DDS的应答器动态检测系统2FSK调制器设计

基于高速综合检测列车平台的应答器动态检测系统可实现对应答器相关设备性能的实时检测。为测试车载应答器动态检测系统的性能,需产生高精度可控波特率和载频的调制信号(2FSK)作为上行链路信号。基于直接数字频率合成器(DDS)技术,通过对相位累加模块和相幅转换模块进行设计,提出分段相位累加算法,计算同周期内相位增量和码元跳变处的相位增量;通过改进的坐标旋转数字计算方法(CORDIC)实时计算对应的信号幅值,用数字模拟转换器(DAC)将离散信号转换为模拟信号,从而实现频偏和数据速率可变且相位连续的信号调制。在相幅转换模块设计中,采用改进CORDIC算法替代传统的查表法,将相位增量转换成信号幅度,有效减少了现场可编程逻辑门阵列(FPGA)存储资源的开销。基于改进DDS的2FSK调制器设计方法,可为应答器动态检测系统提供高精度可控波特率和载频的2FSK调制信号,保证了应答器动态检测系统校准的准确性。

梅山钢铁焦炉煤气DDS生物脱硫技术的应用研究

2022年,上海梅山钢铁股份有限公司焦炉煤气脱硫脱氰(desulfurization and decyanation sorbent,DDS)生物脱硫技术项目成功建设并投入运行。基于此,概述DDS生物脱硫技术的技术核心、技术原理、工艺流程及现场布置,深入分析DDS生物脱硫技术的实际应用与优化、应用效果及应用前景,对项目建设及运行过程中出现的问题进行分析、总结与完善,以期提高企业自身的技术水平,并为其他企业选择煤气脱硫工艺提供了参考。

基于DDS+PLL的频率合成方法研究

针对传统的PLL在小数分频时引起的边界杂散问题,采用DDS作为PLL的参考时钟,通过动态调整DDS的输出频率及PLL的整数分频比,使PLL在整数分频模式下仍具有小步进的合成频率精度。经过理论分析和实测实验验证了方案的可行性,实测实验表明,采用DDS+PLL方案合成频率可以有效解决整数边界杂散,并实现了最大9.31 Hz的频率步进精度。

Rate-limiting factors in hydrate decomposition through depressurization across various scales:A mini-review

Natural gas hydrate is an energy resource for methane that has a carbon quantity twice more than all traditional fossil fuels combined.However,their practical application in the field has been limited due to the challenges of long-term preparation,high costs and associated risks.Experimental studies,on the other hand,offer a safe and cost-effective means of exploring the mechanisms of hydrate dissociation and optimizing exploitation conditions.Gas hydrate decomposition is a complicated process along with intrinsic kinetics,mass transfer and heat transfer,which are the influencing factors for hydrate decomposition rate.The identification of the rate-limiting factor for hydrate dissociation during depressurization varies with the scale of the reservoir,making it challenging to extrapolate findings from laboratory experiments to the actual exploitation.This review aims to summarize current knowledge of investigations on hydrate decomposition on the subject of the research scale(core scale,middle scale,large scale and field tests)and to analyze determining factors for decomposition rate,considering the various research scales and their associated influencing factors.

Scale-space effect and scale hybridization in image intelligent recognition of geological discontinuities on rock slopes

Geological discontinuity(GD)plays a pivotal role in determining the catastrophic mechanical failure of jointed rock masses.Accurate and efficient acquisition of GD networks is essential for characterizing and understanding the progressive damage mechanisms of slopes based on monitoring image data.Inspired by recent advances in computer vision,deep learning(DL)models have been widely utilized for image-based fracture identification.The multi-scale characteristics,image resolution and annotation quality of images will cause a scale-space effect(SSE)that makes features indistinguishable from noise,directly affecting the accuracy.However,this effect has not received adequate attention.Herein,we try to address this gap by collecting slope images at various proportional scales and constructing multi-scale datasets using image processing techniques.Next,we quantify the intensity of feature signals using metrics such as peak signal-to-noise ratio(PSNR)and structural similarity(SSIM).Combining these metrics with the scale-space theory,we investigate the influence of the SSE on the differentiation of multi-scale features and the accuracy of recognition.It is found that augmenting the image's detail capacity does not always yield benefits for vision-based recognition models.In light of these observations,we propose a scale hybridization approach based on the diffusion mechanism of scale-space representation.The results show that scale hybridization strengthens the tolerance of multi-scale feature recognition under complex environmental noise interference and significantly enhances the recognition accuracy of GD.It also facilitates the objective understanding,description and analysis of the rock behavior and stability of slopes from the perspective of image data.

Scale effect removal and range migration correction for hypersonic target coherent detection

The detection of hypersonic targets usually confronts range migration(RM)issue before coherent integration(CI).The traditional methods aiming at correcting RM to obtain CI mainly considers the narrow-band radar condition.However,with the increasing requirement of far-range detection,the time bandwidth product,which is corresponding to radar’s mean power,should be promoted in actual application.Thus,the echo signal generates the scale effect(SE)at large time bandwidth product situation,influencing the intra and inter pulse integration performance.To eliminate SE and correct RM,this paper proposes an effective algorithm,i.e.,scaled location rotation transform(ScLRT).The ScLRT can remove SE to obtain the matching pulse compression(PC)as well as correct RM to complete CI via the location rotation transform,being implemented by seeking the actual rotation angle.Compared to the traditional coherent detection algorithms,Sc LRT can address the SE problem to achieve better detection/estimation capabilities.At last,this paper gives several simulations to assess the viability of ScLRT.

Water as a Standard Substance of a Logarithmic Poison Scale

The lethal dose LD50 represents the most important experimental value for acute toxicity. The simple logarithmic calculation of -log10 LD50 = value leads to the possible poison power pLD. As with the pH or pK value, respectively, for acid or the scale of earthquake intensities the logarithm helps making large differences of orders of magnitude easier to understand since they are more comparable. The higher the pLD value, the higher is the power of poison. An increase of the pLD value by 1 stands for a tenfold increase in toxicity. The lethal acute dose for water, one of the most important and at the same time non-toxic substances of all, is about one tenth of the body weight. This leads to a possible pLD value for water of 1, an ideal starting value for a logarithmic poison scale.

Characterization of Small-Scale Farmers and Assessment of Their Access to Crop Production Information in Selected Counties of Kenya

Small-scale farming accounts for 78% of total agricultural production in Kenya and contributes to 23.5% of the country’s GDP. Their crop production activities are mostly rainfed subsistence with any surplus being sold to bring in some income. Timely decisions on farm practices such as farm preparation and planting are critical determinants of the seasonal outcomes. In Kenya, most small-scale farmers have no reliable source of information that would help them make timely and accurate decisions. County governments have extension officers who are mandated with giving farmers advisory services to farmers but they are not able to reach most farmers due to facilitation constraints. The mode and format of sharing information is also critical since it’s important to ensure that it’s timely, well-understood and usable. This study sought to assess access to geospatial derived and other crop production information by farmers in four selected counties of Kenya. Specific objectives were to determine the profile of small-scale farmers in terms of age, education and farm size;to determine the type of information that is made available to them by County and Sub-County extension officers including the format and mode of provision;and to determine if the information provided was useful in terms of accuracy, timeliness and adequacy. The results indicated that over 80% of the farmers were over 35 years of age and over 56% were male. Majority had attained primary education (34%) or secondary education (29%) and most farmers in all the counties grew maize (71%). Notably, fellow farmers were a source of information (71%) with the frequency of sharing information being mostly seasonal (37%) and when information was available (43%). Over 66% of interviewed farmers indicating that they faced challenges while using provided information. The results from the study are insightful and helpful in determining effective ways of providing farmers with useful information to ensure maximum benefits.

Multi-Time Scale Operation and Simulation Strategy of the Park Based on Model Predictive Control

Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve the expected economy.This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control(MPC).In the day-ahead stage,an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min.In order to cope with power fluctuations of photovoltaic,wind turbine and conventional load,MPC is used to track and roll correct the day-ahead operating simulation plan in the intra-day stage to meet the actual operating operation status of the park.Finally,the validity and economy of the operating simulation strategy are verified through the analysis of arithmetic examples.

Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

Evidence for the Reliability and Validity of the Arabic Version of the Student Risk Screening Scale for Internalizing and Externalizing Behaviors (SRSS-IE)

School-based universal screening for behavioral/emotional risk is a necessary first step to providing services in an educational setting for students with emotional and behavioral disorders (EBDs). Psychometric properties are critical to making decisions about choosing a screening instrument. The purpose of the present study was to examine the psychometric properties of the student risk screening scale for internalizing and externalizing behaviors (SRSS-IE). Participants included 3145 students and their teachers. Item-level analyses of the current sample supported the retention of all items. The internal consistency of the SRSS items ranged from 0.83 to 0.85. Convergent validity between the SRSS-IE and a well-established screening tool, the strength and difficulties questionnaire (SDQ), was found for the total score (r = 0.70). Additionally, the results of this study demonstrate strong social validity, suggesting the SRSS-IE to be a useful and functional screening tool. We conclude that the SRSS-IE is a valid and reliable instrument for assessing the level of emotional and behavioral difficulties among elementary students.

Upsilon Constants and Their Usefulness in Planck Scale Quantum Cosmology

This paper introduces the two Upsilon constants to the reader. Their usefulness is described with respect to acting as coupling constants between the CMB temperature and the Hubble constant. In addition, this paper summarizes the current state of quantum cosmology with respect to the Flat Space Cosmology (FSC) model. Although the FSC quantum cosmology formulae were published in 2018, they are only rearrangements and substitutions of the other assumptions into the original FSC Hubble temperature formula. In a real sense, this temperature formula was the first quantum cosmology formula developed since Hawking’s black hole temperature formula. A recent development in the last month proves that the FSC Hubble temperature formula can be derived from the Stephan-Boltzmann law. Thus, this Hubble temperature formula effectively unites some quantum developments with the general relativity model inherent in FSC. More progress towards unification in the near-future is expected.

基于DDS的分布式自动航空电子测试系统的设计和实现

针对综合化航电系统测试数据量大、测试控制复杂的问题,设计开发了基于数据分发服务(DDS)的自动分布式航空电子测试系统,以实现分布式测试控制和自动测试控制。同时定义了基于IEEE1671的测试接口定义,用于为用户提供统一的测试接口。

Foundations of the Scale-Symmetric Theory and the Illusory Total Width of the Off-Shell Higgs Bosons

Here we present the foundations of the Scale-Symmetric Theory (SST), i.e. the fundamental phase transitions of the initial inflation field, the atom-like structure of baryons and different types of black holes. Within SST we show that the transition from the nuclear strong interactions in the off-shell Higgs boson production to the nuclear weak interactions causes that the real total width of the Higgs boson from the Higgs line shape (i.e. 3.3 GeV) decreases to 4.3 MeV that is the illusory total width. Moreover, there appear some glueballs/condensates with the energy 3.3 GeV that accompany the production of the off-shell Higgs bosons.

A Lightweight Convolutional Neural Network with Hierarchical Multi-Scale Feature Fusion for Image Classification

Convolutional neural networks (CNNs) are widely used in image classification tasks, but their increasing model size and computation make them challenging to implement on embedded systems with constrained hardware resources. To address this issue, the MobileNetV1 network was developed, which employs depthwise convolution to reduce network complexity. MobileNetV1 employs a stride of 2 in several convolutional layers to decrease the spatial resolution of feature maps, thereby lowering computational costs. However, this stride setting can lead to a loss of spatial information, particularly affecting the detection and representation of smaller objects or finer details in images. To maintain the trade-off between complexity and model performance, a lightweight convolutional neural network with hierarchical multi-scale feature fusion based on the MobileNetV1 network is proposed. The network consists of two main subnetworks. The first subnetwork uses a depthwise dilated separable convolution (DDSC) layer to learn imaging features with fewer parameters, which results in a lightweight and computationally inexpensive network. Furthermore, depthwise dilated convolution in DDSC layer effectively expands the field of view of filters, allowing them to incorporate a larger context. The second subnetwork is a hierarchical multi-scale feature fusion (HMFF) module that uses parallel multi-resolution branches architecture to process the input feature map in order to extract the multi-scale feature information of the input image. Experimental results on the CIFAR-10, Malaria, and KvasirV1 datasets demonstrate that the proposed method is efficient, reducing the network parameters and computational cost by 65.02% and 39.78%, respectively, while maintaining the network performance compared to the MobileNetV1 baseline.

基于DDS协议的离岸船舶实时定位方法

为提升离岸船舶实时定位效果、确保船舶航行安全,提出基于DDS协议的离岸船舶实时定位方法。在离岸船舶上安装移动阅读器,在航道两侧安装固定标签。利用改进加权质心定位算法,结合移动阅读器与固定标签间接收信号强度值,计算移动阅读器的位置信息,即离岸船舶实时位置信息。利用DDS协议信息分发单元启动分发服务,将位置信息传输至全局数据空间内,再利用空间内的缓存移动阅读器发布实时位置信息。最后,服务器通过调用DDS接口订阅或退订全局数据空间内缓存的信息,并由显示器呈现订阅的离岸船舶实时位置信息。实验证明:该方法可精准实时定位离岸船舶;当信息分发量不同时,该方法的信息分发丢包率较低。

基于FPGA的DDS信号发生器设计

函数信号发生器作为信号源,广泛的应用于课堂教学,研究试验和工业生产等各个领域。通过MCU与FPGA的硬件结合方式,由MCU负责输入输出的人机交互控制,FPGA负责实现核心DDS技术。然后对输出的波形做相关性能测试实验,正弦波的THD计算和三角波的线性度计算。测试结果表明,该信号发生器参数可调范围宽,精度高,稳定可靠,具有一定的实用价值。同时说明了MCU与FPGA联合使用的这种硬件框架是稳定可靠的,是可以应用到大部分的微控制系统中的,也为进一步应用提供了重要的参考依据。

基于边缘计算DDS动态域标识近距轮询网络应用研究

智能汽车、无人机或工业智能化生产线,在边缘计算提供的共享式传感网和共享式算力资源帮助下,能够有效降低成本,扩大感知范围。传统的通信网络虽然实现了全球统一的广域连接,但在动态更新局部域通信过程中,远距离的传感器对于受控对象所处空间控制的意义并不大。为了提高区域通信的实时响应,通信网络需要随着汽车、无人机或生产线物流的空间位置变化进行动态局部组网。基于此,本文介绍了一种新型的边缘计算分布式通信网络,提出了动态更新域标识架构,该架构内的各终端节点根据空间所处位置自动地构造局域通信簇,并基于该簇进行动态轮询访问。该方法能够实现近距共享传感器和人工智能算力,降低了单机智能化成本,对于人工智能项目落地和技术推广具有一定的促进意义。