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关键词： Impedance   Resonant frequency   Antennas   Substrates   Strips   Slot antennas   Wideband   RFID tag   UHF   wideband   long range   metallic object  

摘要： A folded-patch tag antenna measuring ( $53.5\times 12\times 3.3$ ) mm3 has been developed for effective operation on metallic surfaces. The antenna design features a distinctive serrated triangular patch radiator on its top layer, connected to the bottom ground plane through inductive stubs positioned at the ends. This triangular patch configuration is tailored to offer enhanced impedance matching. Furthermore, the inclusion of serrations, inductive stubs, and a thin rectangular stub on the top layer serves the dual purpose of fine-tuning the resonant frequency and reducing the overall size of the tag. The designed tag antenna works well for both ETSI and FCC bands. In practical testing scenarios in ETSI band, the designed tag antenna achieves a maximum read range of 8 meters in air and 5.1 meters when mounted on a metallic plate of size $20\times 20$ cm2. For FCC band the read range is 4.5 m in air and 3.1 m for metallic surface. The tag also exhibit 4 m (ETSI) and 2.1 m (FCC) reading ranges on curved metallic surface. Notably, the wide operational frequency range of the tag encompasses both European/Indian and U.S. RFID bands.

关键词： 轨道物流传输   LORA   RFID   RTOS   Floyd算法  

摘要： 随着医疗技术的不断进步和医院规模的扩大,医院传统以人力操作为主导的物流运输方式已无法满足医院智能、高效的需求。近年来,轨道物流系统以其空间占用小、传输容量大、智能化程度高等优势,在医疗领域得到了广泛的关注和应用。 针对目前医用轨道物流系统大多采用轨道供电和有线通信方式,且小车运行过程状态远程监控能力不足,并对于液态运输物资运输过程的平稳性缺乏有效的保证手段等现状问题。本文致力于设计并开发一种新型的轨道物流系统,采用电池供电、LORA无线通讯等解决方案,并实现小车自平衡运输等目标,从而更全面地满足医用物流的多样化需求。本论文主要的工作如下: (1)机械结构方面,完成了轨道、轨道机器人、平行转轨器、十字转轨器等关键传输设备的机械结构设计,构建了医院应用场景地图模型,搭建了轨道物流传输系统验证模型。 (2)通信方式上,通过比较三种无线通信方式,最终选择了更能适应楼宇场景的LORA通信作为连接控制中心与轨道机器人之间的通信方式,且对控制中心、转轨器、轨道机器人之间交互协议进行设计。并针对通信过程中存在的干扰问题,设计了一种可靠传输机制。在定位方式方面,以设计的四类RFID标签为基础构建物流轨道传输系统的电子地图。 (3)根据系统的总体需求,给出了物流机器人与转轨器的硬件设计和外设方案。在移植了Free RTOS的基础上,完成了轨道机器人与转轨器的各个模块软件设计并绘制了流程图。利用倾角传感器与旋转电机实现了的轨道机器人的自平衡功能,且通过对轨道机器人实际运行情况建立了状态模型。 (4)对总控调度层软件进行了设计,详细探究了轨道机器人与转轨器、轨道机器人与控制中心以及控制中心与转轨器之间的通信过程。并以Floyd算法为基础,讨论了单车调度和多车调度问题,提出了建立临时停靠站点、转轨器优化等解决方案。 (5)完成了轨道传输系统的通信与控制系统的基本测试和验证,论证了系统设计方案的可行性,初步展现了控制系统的运行效果。

关键词： 大数据   RFID技术   电能计量资产   寿命期限预警   引入扰动系数   状态数据  

摘要： 由于电能计量资产的期限寿命受历史状态和当前状态等因素综合影响，导致预警结果的误差难以得到有效控制，为此，本文提出基于大数据和无线射频识别(RFID)技术的电能计量资产寿命期限预警方法研究。研究利用RFID技术，开展电能计量资产状态数据(实时读数、历史数据、校准信息)的采集，通过引入扰动系数对状态数据影响期限寿命的程度进行分析，构建了电能计量资产寿命期限预警模型。在测试结果中，不同的电能计量资产寿命期限的预警结果与实际情况的误差始终在5.0天以内。

关键词： reader   tag   authentication   RFID   IoT   elliptical curves  

摘要： The Internet of Things (IoT) has now permeated every aspect of modern life, requiring that all things be connected to one another and to the Internet using proper protocols. IoT, being an essential component of today's smart society is experiencing enormous problems from various security and interoperability attacks. Traditional encryption is unsuitable for low-cost IoTs because they are vulnerable to physical attacks. This paper proposes Lightweight mutual Authentication Protocol for IoT devices based on hash function using Elliptical Curve approach in which mutual authentication between RFID Tag and Reader is established through several rounds of communication. We also compare the proposed approach of authentication at both ends (Tag and Reader) in terms of efficiency and security.

关键词： RFID物联网   创新技术   档案管理  

摘要： 随着物联网技术日趋成熟，物联网技术实现了物体之间的互联互通，极大地提高了信息的获取和处理能力，随着RFID物联网创新技术的档案管理系统应用，有着良好的发展前景，有利于促进档案管理工作的高效性和智能化。本课题从档案管理的存在的问题进行分析，对RFID物联网的档案管理系统的研究与设计优势进行研究探讨，进而实现档案管理全过程的自动化、智能化，进而实现RFID物联网创新技术的档案管理系统应用的价值和应用前景。

关键词： Sign language   Radiofrequency identification   Accuracy   RF signals   Assistive technologies   Wireless fidelity   Wearable sensors   Standards   Noise   Cameras   Sign language recognition   signal segmentation   RFID   CNN   BiLSTM  

摘要： As the number of individuals with speech and hearing impairments continues to grow, the demand for sign language recognition systems is increasing. Furthermore, most radio frequency-based gesture recognition systems have primarily focused on simple gestures, neglecting more complex actions such as sign language. Therefore, this paper proposes RF-SL, a commercial RFID-based contactless sign language recognition system. This system does not require users to wear any tags and only requires them to perform sign language gestures positioned between an antenna and a fixed multi-tag array to collect sign language signals. Firstly, by removing static reflection noise, we reduce the impact of environmental noise and obtain purer data. Secondly, to accurately delineate the start and end points of sign language action signals, we propose an improved version of the Varri signal segmentation algorithm called Varri+ to effectively optimize the segmentation of sign language actions. Thirdly, we combine the CNN model, known for its robust feature extraction capabilities, with the BiLSTM model, which excels in feature fusion. Extensive testing and evaluation were conducted in two realistic scenarios. The experimental results show that RF-SL achieves an overall average recognition accuracy of 96.8%, with an average recognition accuracy of 96.3% for new users. Additionally, RF-SL achieves an F1 score of 97.5% in an empty room with the weak multipath effects and an F1 score of 93.6% in a classroom with the strong multipath effects. These results demonstrate that our system is dynamic, flexible and robust in sign language recognition.

关键词： 无源UHF RFID标签芯片   射频前端   解调电路   高灵敏度   浅调制  

摘要： 随着移动互联网及信息传感技术的不断发展,RFID电子标签在仓储物流管理、交通运输、生物医学等多个领域广泛使用,无源UHF RFID电子标签因其较远的识别距离和低成本的优势成为了目前RFID应用和研究的重要实施方向。对于无源UHF RFID标签芯片来说,射频前端作为整个芯片能量传输和数据传输的关键模块,其电路结构及性能将直接影响整个芯片的识别性能。 本文通过对无源UHF RFID标签芯片结构原理以及相关协议要求的分析,对射频前端数据传输链路的解调和调制电路进行了设计。重点针对射频浅调制信号,对射频前端数据传输前向链路中的解调电路灵敏度、动态范围、调制指数等性能参数进行了优化设计。此外还设计了一种适用于能量收集系统的低压低功耗亚阈值全MOS基准电路,以产生芯片其他模块所需的电压和电流。 针对浅调制信号的解调,为了实现较高的解调灵敏度,采用了有源偏罝对检波管进行阈值补偿,提高了解调电路的检波灵敏度,使芯片在远距离通信时仍能对信号进行解调,同时采用了限压泄流电路使得电路可以在近场时正常工作,提高了信号的动态范围。为了进一步提高解调电路对于浅调制信号的解调性能,采用均值检测电路对参考电平进行提取,同时采用了包络放大器对峰值小于160mV的信号进行放大,使均值检测电路能够更加准确的提取包络信号的均值,该方法在提高灵敏度的同时避免了因信号幅度过小而导致均值电平误差过大,进而导致解调误差过大甚至无法解调的问题。针对系统低压低功耗的需求,设计了一种亚阈值全MOS基准电路,输出基准电压采用不同阈值电压的MOS管来产生,具有较小的工艺偏差。在数据传输的反向链路中,设计了一种利用开关来实现的简单 ASK调制反射电路,在实现信号调号调制的同时不产生额外功耗。 基于UMC110nm工艺实现电路设计,射频/模拟前端电源电压为1V,通过Cadence Specture平台进行了电路原理图设计及前仿真、版图绘制及后仿真验证。最终浅调制解调电路在输入射频载波频率为920MHz,数据调制速率为40～160kHz时,实现了最小幅值为35mV,动态范围为0.035～1V,最小调制指数为30%的信号解调。当输入射频信号幅值为400mV、工作温度27℃时,解调电路在不同工艺角下最大功耗为2.9μW。该解调电路不仅能够适用于远距离通信,对于不同协议下不同调制深度的信号也具有较好的适用性。亚阈值基准电路输出基准电压及电流对电源电压波动均有较好的抑制能力,整个基准电路功耗仅为343nW。调制电路在射频信号的整个动态范围内都可以实现数据的准确调制,且对不同的协议具有通用性。

关键词： RGV   视觉引导   RFID   SINS   自适应卡尔曼滤波   组合定位  

摘要： 随着我国经济的发展和现代化建设进程的加快,对隧道工程建设中物料运输的效率与安全性也提出越来越高的要求,RGV(有轨穿梭小车)应用于隧道施工的物料运输已成为大势所趋,RGV较适合长距离运输并且载重能力强、运行速度快。可以十分便捷高效地按照计划进行物料的输送。隧道内RGV的自主导航研究是RGV运载性能进一步提升和拓展的关键。本文设计了一种隧道内RGV导航方法,主要包括基于轨道状态识别的视觉引导方法和基于RFID/SINS数据融合的组合定位方法,分别实现了RGV的路径指引和提供实时高精度位置信息的功能,通过仿真验证了本文提出的隧道内RGV导航方法的有效性。本文主要做了以下工作: 在视觉引导部分,基于隧道内RGV有轨运行的特点,对RGV车载相机采集的前方轨道图像进行识别提取出轨道的关键特征参数,提供给RGV行驶控制模块正确的指令信息。该算法可检测出轨道中存在的障碍物并对RGV的控制系统发送预警信号,保证行车的安全性;针对轨道类型的判别问题,提出了一种求取二值化图像复杂度的方法和逆透视变换结合垂直像素投影的方法对直轨、弯轨与和道岔进行判别区分,根据判别结果选择不同的处理算法;针对固定半径曲线弯轨检测,提出了一种对垂直像素投影分段求取均值与求取梯度极值的方法提取直轨与弯轨的分界点,精确提取弯道拟合像素点集,大大提高了最小二乘法圆拟合的精确度和抗干扰性,基于此分界点还可对与弯轨相连的直轨长度进行测算,从而得到RGV到拐弯点的距离;针对道岔检测,提出了一种基于Hough直线检测对道岔区域进行自适应ROI提取的方法,并结合逆透视变换与垂直像素投影判断道岔的连接状态,为RGV行驶提供正确指令。 针对单一使用捷联式惯性导航系统(SINS)进行定位会导致误差累计的问题,本文提出了一种利用射频识别技术进行位置修正的隧道内RGV定位系统,系统将射频标签存储的经纬度位置信息和SINS解算位置的差值作为量测量,利用自适应卡尔曼滤波算法进行数据融合,该方法在常规卡尔曼滤波的基础上增加了对时变噪声的调整,允许系统实时优化测量噪声矩阵,对SINS中的陀螺仪漂移和加速度计偏差进行有效修正。实际测试结果表明,这种方法能够显著提升定位的准确性和系统的稳定性。通过仿真模拟不同RFID标签布置间隔的导航策略,进行结果分析和数据比较后确定了理想的修正间隔。

关键词： Chipless radio frequency identification (CRFID)   convolutional neural networks (CNN)   deep learning (DL)   electromagnetics (EMs)   machine learning (ML)   radar cross section (RCS)   radio frequency identification (RFID)   robots  

摘要： In this article, we present a new approach for robust reading of identification (ID) and sensor data from chipless radio frequency ID (CRFID) sensor tags. For the first time, machine-learning (ML) and deep-learning (DL) regression modeling techniques are applied to a dataset of measured radar cross Section (RCS) data that have been derived from large-scale robotic measurements of custom-designed, 3-bit CRFID sensor tags. The robotic system is implemented using the first-of-its-kind automated data acquisition method using an ur16e industry-standard robot. A dataset of 9600 electromagnetic (EM) RCS signatures collected using the automated system is used to train and validate four ML models and four 1-D convolutional neural network (1-D CNN) architectures. For the first time, we report an end-to-end design and implementation methodology for robust detection of ID and sensing data using ML/DL models. Also, we report, for the first time, the effect of varying tag surface shapes, tilt angles, and read ranges that were incorporated into the training of models for robust detection of ID and sensing values. The results show that all the models were able to generalize well on the given data. However, the 1-D CNN models outperformed the conventional ML models in the detection of ID and sensing values. The best 1-D CNN model architectures performed well with a low root-mean-square error (RMSE) of 0.061 (0.87%) for tag ID and 0.0241 (3.44%) error for capacitive sensing.

关键词： Climate change   Radiofrequency identification   Environmental factors   Life cycle assessment   UHF communication   Global warming   RFID tags   Chipless RFID   environmental impacts   life cycle assessment   RFID  

摘要： A Life Cycle Assessment (LCA) is performed to evaluate the environmental impact of chipless RFID using the standardized LCA method. This allows for a comparison of these impacts with those of UHF RFID and barcode technologies. Identification technologies such as RFID (UHF, HF) are intended to be disseminated worldwide to the greatest number of people and therefore to generate the use of a very large number of tags. Thus, several billion UHF and HF labels are produced per year. Insofar as the lifespan of these labels is short and therefore can be considered disposable components, it is vital to measure their impact on the environment. This is not only due to the growing concerns about global warming but also to explore alternatives to RFID tags that can help conserve resources and reduce pollution. This study allows us to evaluate the environmental impact and carbon footprint. The results of this research will provide new insights and suggest ways to reduce the environmental impact of the electronics industry.