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关键词： computer networks   distribution networks   learning (artificial intelligence)   power cable insulation  

摘要： This research addresses the challenge faced by most existing prediction methods in handling nonlinear data of cables. Furthermore, it proposes a novel power cable monitoring method utilizing UHF-RFID and deep learning within an edge computing environment, specifically targeting the currently suboptimal wireless monitoring of cables. First, based on edge computing, a power cable monitoring system is designed to migrate the analysis of massive data to the edge of the network to improve the monitoring efficiency. Then, the temperature sensing chip and RFID chip were integrated to design a UHF-RFID temperature tag, which was fixed at the cable temperature measurement point to achieve passive wireless monitoring of the cable. Finally, the parameters of the GRNN model are optimized using the beetle antennae search algorithm, and the EEMD decomposed data is input into the BAS-GRNN model for learning to output temperature prediction results. Based on the establishment of an experimental platform, the method was demonstrated, and results showed that the maximum error between the UHF-RFID temperature tag temperature measurement results and the thermocouple was within 0.3 degrees C, and the average relative error of the proposed method was only 0.01, which can meet the accuracy requirements of actual monitoring of power cables. In order to solve the problems of the current wireless cable monitoring effect is not ideal and the prediction method is difficult to deal with the nonlinear data of cables, a power cable monitoring method based on UHF-RFID and deep learning in the edge computing environment is proposed. image

关键词： Nondestructive examination  

摘要： The application of the UHF RFID technique in non-destructive testing (NDT) and structural health monitoring (SHM) has gained increasing attention due to its wireless, battery-less, and cost-effective attributes. It offers a promising approach for SHM and Internet of Things (IoTs). This paper reports commercial off-the-shelf (COTS) flexible UHF RFID tag-based sensors for corrosion characterization on coated mild steel. Two types of COTS flexible UHF RFID tags with different bends are fabricated as sensors. The received signal strength indicator (RSSI) measurement is implemented to characterize the corrosion. Three parts (T-match area, dipole arms, and dipole-loadings) of the two tags are tested for sensing purpose, and a comparison and discussion of sensitivity, read range, and results are provided. This study successfully validates the feasibility of the proposed tag-bent method for corrosion characterization undercoating. It can be concluded that the dipole arm part of the applied COTS tags is the most sensitive area. © 2024, The Authors. All rights reserved.

关键词： Real time systems  

摘要： In many RFID-enabled applications, objects are classified into different categories, and the information associated with each object's category (called category information) is written into the attached tag, allowing the reader to access it later. The category information sampling in such RFID systems, which is to randomly choose (sample) a few tags from each category and collect their category information, is fundamental for providing real-time monitoring and analysis in RFID. However, to the best of our knowledge, two technical challenges, i.e., how to guarantee a minimized execution time and reduce collection failure caused by missing tags, remain unsolved for this problem. In this paper, we address these two limitations by considering how to use the shortest possible time to sample a different number of random tags from each category and collect their category information sequentially in small batches. In particular, we first obtain a lower bound on the execution time of any protocol that can solve this problem. Then, we present a near- OPTimal Category information sampling protocol (OPT-C) that solves the problem with an execution time close to the lower bound. Finally, extensive simulation results demonstrate the superiority of OPT-C over existing protocols, while real-world experiments validate the practicality of OPT-C. Copyright © 2024, The Authors. All rights reserved.

关键词： RFID技术   图书馆   智能管理   应用研究  

摘要： 近年来,射频识别(Radio Frequency Indentification,RFID)技术在高校图书馆领域引发了广泛关注。文章以南京特殊教育师范学院图书馆的RFID项目为实例,深入探讨了该项目的概况和实施过程,并详细介绍了RFID技术在馆藏书库管理、借还书流程管理、图书定位查询以及图书防盗4个方面的应用情况。同时,文章深入分析了RFID技术在图书信息盘点、维护运行、技术成本、信号干扰以及馆员培训等方面所存在的局限性和挑战。文章提出了针对RFID应用的相关建议,旨在为RFID技术的研发者和后续使用者提供有益的参考和启示。

关键词： 多目标定位   射频识别(RFID)   相控阵   反射式移相  

摘要： 室内定位有多种方案,如蓝牙到达角度(Angle of Arrival,AOA)、Wi-Fi、接收信号强度指示(Received Signal Strength Indication,RSSI)及超宽带(Ultra Wide Band,UWB)等。在多目标定位、低成本、低功耗场景下,超高频无源射频识别(Radio Frequency Identification,RFID)具有显著优势。为实现室内多物品快速定位,将超高频无源RFID技术与相控阵技术相融合,建立一套室内定位系统。

关键词： 数字水印   二维码   云平台   智能包装   防伪追溯   应用物理   一物一码   RFID  

摘要： 综合应用物理防伪、数字水印、一物一码技术,构建防伪追溯数字云平台,提供智能包装整体解决方案。你听说过智能包装吗?眼前看到的纸盒,拿出手机扫一扫,智能包装瞬间就可以带你进入一个立体的世界,参与到奇妙的互动与体验之中,而它背后离不开先进技术的加持,比如二维码、RFID、NFC、AR增强现实等。今天故事的主人公——四川天星智能包装股份有限公司(以下简称天星股份)就是这样一个“技术大咖”。

关键词： 射频识别   精密   纠偏系统   门式起重机   安全  

摘要： 针对某码头门式起重机纠偏系统的检测计算误差较大问题,通过将射频识别(RFID)技术整合到门式起重机的精密纠偏系统中,提高系统的纠偏精度和可靠性;通过预警和报警机制提供及时反馈,减少因设备故障导致的停机时间,提高生产效率,降低维护成本。

关键词： 棉花加工企业   质量追溯   棉花质量   数据统计   安全监管   质量提升   货场管理   籽棉  

摘要： 棉花质量追溯是完善棉花目标价格政策的重要内容,是实施棉花质量补贴的具体手段,是促进棉花质量提升的重要措施。当前棉花加工企业籽棉收购期间厂区内堆垛方式比较随意,管理相对粗放,籽棉货场管理主要通过人工巡检记录,不便于数据统计以及实时了解加工企业厂区内籽棉存放和加工情况。在需要加工时不能准确地抓取所需指标的棉模,水分杂质较高的棉模也存在自燃、捂坏变质的安全隐患,企业缺乏有效的安全监管办法。

关键词： 物联网技术   射频识别   电子标签   PID控制   楼宇智能控制  

摘要： 当前系统控制效果差,智能化程度低,为此设计基于物联网技术的医院楼宇智能控制系统。物联网模块包括射频识别、网络传感器等单元,选择两种总线进行数据通信,以ARM构架为基础设计控制器芯片,通过对继电反馈PID控制算法实施PID参数求解,实现各种系统运行调度控制,通过智能策略模块,设置各种系统设备的开关状态,并采用在某大型医院作为测试对象,结果表明,所设计系统能够实现送排风系统、电梯系统、消防系统的全面智能控制,可以有效节省医院建筑电力消耗,具有较高的实际应用价值。

关键词： 通信技术   射频识别标签天线   改进遗传算法-反向传播算法   Adagrad优化器  

摘要： 为了提高算法对天线参数的预测精度,提出了一种基于Adagrad优化器的改进遗传算法-反向传播(GA-BP)算法。通过在迭代过程中引入Adagrad优化器与阈值策略,对发生退化的种群最优个体的位置信息进行重新引导,解决了GA-BP算法局部寻优能力不足等问题,大幅度减小了误差损失并且加快了收敛速度。利用该方法对射频识别(RFID)标签天线的印刷品质和电磁参数进行了建模与分析。结果表明,改进GA-BP算法在稳步搜索极值的同时可以避免陷入局部极值陷阱,在误差和收敛效率方面均优于传统的反向传播(BP)算法与GA-BP算法,能够得到较高的预测精度,实现了RFID标签天线印刷品质的优化控制以及S_(11)特征曲线的预测。相比于BP算法与GA-BP算法,改进GA-BP算法在用于优化RFID标签天线的印刷品质时,平均绝对误差分别降低了91.92%和85.64%。在电磁参数预测应用时,分别降低了13.77%和13.19%。