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1.
朱佩佩 《电讯技术》2022,62(3):342-347
电力线是一类形状细长、特征稀疏、随着视角的变化容易混淆在大量背景信息中的特殊障碍物,常规电力线检测识别算法得到的目标框对电力线所在位置的估计不够准确。为此,提出了一种相对角度估计方法,基于常规电力线目标检测与识别算法,并结合电力线相对角度估计,从而提高电力线的检测识别过程中所在位置的精度。相比电力线绝对角度回归的方法,提出的相对角度估计方法容易训练易收敛,计算量小,适用于实时性要求较高的应用场合。  相似文献   
2.
We propose a self-sustaining power supply system consisting of a “Hybrid Energy Storage System (HESS)” and renewable energy sources to ensure a stable supply of high-quality power in remote islands. The configuration of the self-sustaining power supply system that can utilize renewable energy sources effectively on remote islands where the installation area is limited is investigated. It is found that it is important to select renewable energy sources whose output power curve is close to the load curve to improve the efficiency of the system. The operation methods that can increase the cost-effectiveness of the self-sustaining power supply system are also investigated. It is clarified that it is important for increasing the cost effectiveness of the self-sustaining power supply system to operate the HESS with a smaller capacity of its components by setting upper limits on the output power of the renewable energy sources and cutting the infrequent generated power.  相似文献   
3.
以智能反射面(intelligent reflecting surface,IRS)辅助的无线携能通信(simultaneous wireless information and power transfer,SWIPT)系统为背景,研究了该系统中基于能效优先的多天线发送端有源波束成形与IRS无源波束成形联合设计与优化方法。以最大化接收端的最小能效为优化目标,构造在发送端功率、接收端能量阈值、IRS相移等多约束下的非线性优化问题,用交替方向乘子法(alternating direction method of multipliers,ADMM)求解。采用Dinkelbach算法转化目标函数,通过奇异值分解(singular value decomposition,SVD)和半定松弛(semi-definite relaxation,SDR)得到发送端有源波束成形向量。采用SDR得到IRS相移矩阵与反射波束成形向量。结果表明,该系统显著降低了系统能量收集(energy harvesting,EH)接收端的能量阈值。当系统总电路功耗为?15 dBm时,所提方案的用户能效为300 KB/J。当IRS反射阵源数与发送天线数均为最大值时,系统可达最大能效。  相似文献   
4.
This study represents the results of the analysis and optimization of an integrated system for cogenerating electricity and freshwater. This setup consists of a Solid Oxide Fuel cell (SOFC) for producing electricity. Unburned fuel of the SOFC is burned in the afterburner to increase the temperature of the SOFC's outlet gasses and operate a Gas turbine (GT) to produce additional power and operate the air compressor. At the bottom of this cycle, a combined setup of a Multi-Effect Desalination (MED) and Reverse Osmosis (RO) is considered to produce freshwater from the unused heat capacity of the GT's exhaust gasses. Also, a Stirling engine is used in the fuel supply line to increase the fuel's temperature. Using LNG and the Stirling engine will replace the fuel compressor with a pump which increases the system performance and eliminates the need for the expansion valve. To study the system performance a mathematical model is developed in Engineering Equation Solver (EES) program. Then, the system's simulated data from the EES has been sent to MATLAB to promote the best operating condition based on the optimization criteria. An energetic, exergetic, economic, and environmental analysis has been performed and a Non-dominated Sorting Genetic Algorithm (NSGA-II) is used to achieve the goal. The two-objective optimization is performed to maximize the exergetic efficiency of the proposed system while minimizing the system's total cost of production. This cost is a weighted distribution of the Levelized Cost of Electricity (LCOE) and Levelized Cost of freshwater (LCOW). The results showed that the exergetic and energetic efficiencies of the system can reach 73.5% and 69.06% at the optimum point. The total electricity production of the system is 99 MW. The production cost is 11.71 Cents/kWh, of which 1.04 Cents/kWh is emission-related and environmental taxes. The freshwater production rate is 42.44 kg/s which costs 4.38 USD/m3.  相似文献   
5.
Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).  相似文献   
6.
提出了一种镁合金管材转角焊合室分流挤压新工艺,该工艺可在有效延长焊合室长度和焊合时间前提下保证舌针刚度,从而保证管材尺寸精度,并且可通过转角剪切变形机制增加预焊合金属变形量和动态再结晶程度,从而有利于提高管材性能和焊缝焊合性能。利用有限元法揭示了转角焊合室分流挤压成形过程中金属的流动特征,应变分布特征和焊合室内的静水压力分布特征。结果表明,整个挤压过程无金属折叠,从而保证管材的表面质量;流经转角后预焊合金属变形量明显增加,有利于提高管材质量和焊缝质量。最后,研究揭示了坯料初始温度,挤压速度和模具转角对焊合室内静水压力的影响规律。结果表明,随着挤压速度的增加和模具转角的增大,转角焊合室内静水压力增大;随着坯料预热温度的增加,转角焊合室内静水压力呈先增大后减小的趋势。  相似文献   
7.
多堆厂址一级概率安全评价(PSA)研究中,机组数目的增加使得建模工作量剧增,给整个核电厂的风险评估带来困难。结合已有基础,本文研究了多堆厂址始发事件分析的筛选方法,提出利用堆芯损伤频率(CDF)上下限值评估方法,分析厂址内不同机组数对厂址CDF的影响。结果表明,双机组厂址适合优先进行具体分析。针对双机组核电站,对多堆厂址内各始发事件进行筛选。结果表明,丧失厂外电、丧失热阱等事件适合建模分析,并对其他筛选结果给出后续分析建议,为多堆厂址一级PSA后续事故序列建模工作提供了重要基础。  相似文献   
8.
A sustainable power source is a key technical challenge for practical applications of electrically responsive soft robots, especially the required voltage is over several thousand volts. Here, a practicable new technology, triboelectric soft robot (TESR) system with the primary characteristics of power source from mechanical energy, is developed. At its heart is TESR with bioinspired architectures made of soft-deformable body and two triboelectric adhesion feet, which is driven and accurately controlled through triboelectric effect, while reaching maximum crawling speeds of 14.9 mm s−1 on the acrylic surface. The characteristics of the TESR, including displacement and force, are tested and simulated under the power of a rotary freestanding triboelectric nanogenerator (RF-TENG). Crawling of TESR is successfully realized on different materials surfaces and different angle slopes under the driven of RF-TENG. Furthermore, a real-time visual monitoring platform, in which TESR carries a micro camera to transmit images in a long narrow tunnel, is also achieved successfully, indicating that it can be used for fast diagnosis in an area inaccessible to human beings in the future. This study offers a new insight into the sustainable power source technologies suitable for electrically responsive soft robots and contributes to expanding the applicability of TENGs.  相似文献   
9.
归一化水体指数(NDWI)是水体遥感反演的一种重要指标,其阈值及修正直接影响反演结果的精度。基于Landsat-8与GF-1光学多光谱影像,使用归一化水体指数法阈值0(TH0)、最大类间方差法(OTSU)自适应阈值(THotsu)与均值漂移聚类算法(Mean-Shift)自适应阈值(THMS)分别对典型正常水体、云雾覆盖水体、富营养化水体、高含泥沙水体进行水体遥感提取与效果分析,结果表明:正常水体以TH0为阈值提取精度最高,THMS提取精度次之,THotsu提取精度最差;而云雾覆盖水体、富营养化水体以及含泥沙水体使用THMS提取精度最高,尤其少量云雾覆盖下的水体,THMS具有更明显的优势,TH0提取精度次之,THotsu提取精度最差;对于不同的阈值,Land?sat-8比GF-1总体表现出更高的水体提取精度。Mean-Shift算法应用于NDWI阈值修正与水体遥感反演具有快速、水质适应性强、效果稳定的优势,对尤其是复杂条件下的水体信息遥感反演具有较好的提取效果。  相似文献   
10.
现有文献针对计及转子变流器(RSC)控制的双馈感应风电机组(DFIG)定子短路电流解析表达,将定子磁链当作一阶直流衰减分量或忽略功率外环控制。基于DFIG电压、磁链和RSC控制方程,得到定子电流关于定子电压和定子功率的传递函数,提出定子电流的精确解析表达式。基于RSC内、外环PI参数关系,推导直流分量衰减时间常数和角频率关于PI参数的表达式。分析了RSC内外环PI参数对定子电流直流衰减分量的影响。仿真结果验证了解析表达式的准确性,为PI参数选取和保护装置测量、整定提供依据。  相似文献   
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