Durable Integrated K-Metal Anode with Enhanced Mass Transport through Potassiphilic Porous Interconnected Mediator

K-metal batteries have become one of the promising candidates for the large-scale energy storage owing to the virtually inexhaustible and widely potassium resources. The uneven K⁺ deposition and dendrite growth on the anode causes the batteries prematurely failure to limit the further application. An integrated K-metal anode is constructed by cold-rolling K metal with a potassiphilic porous interconnected mediator. Based on the experimental results and theoretical calculations, it demonstrates that the potassiphilic porous interconnected mediator boosts the mass transportation of K-metal anode by the K affinity enhancement, which decreases the concentration polarization and makes a dendrite-free K-metal anode interface. The interconnected porous structure mitigates the internal stress generated during repetitive deposition/stripping, enabling minimized the generation of electrode collapse. As a result, a durable K-metal anode with excellent cycling ability of exceed 1, 000 h at 1 mA cm⁻²/1 mAh cm⁻² and lower polarization voltage in carbonate electrolyte is obtained. This proposed integrated anode with fast K⁺ kinetics fabricated by a repeated cold rolling and folding process provides a new avenue for constructing a high-performance dendrites-free anode for K-metal batteries.     

Adaptive fixed-time prescribed performance control of vehicular platoons with unknown dead-zone and actuator saturation

This article focuses on the problem of fixed-time prescribed performance platoon control for heterogeneous vehicles with unknown dead-zone and actuator saturation. First, an equivalent transformation is developed to approximate the actuator nonlinearity (i.e., dead-zone and saturation), which reduces the complexity of controller design. Then, to guarantee the tracking errors converge to the predetermined region in the given time, a modified prescribed performance function is presented. Based on this, a novel adaptive sliding mode control scheme is developed in the context of fixed-time theory, which is proved to be capable of ensuring individual vehicle stability and string stability in fixed time. In addition, under the proposed control scheme, the convergence time is independent of initial conditions of the system. Finally, numerical simulations are carried out to demonstrate the effectiveness of the proposed control scheme.     

Robust integrated sequential covariance intersection fusion Kalman filters and their convergence and stability for networked sensor systems with five uncertainties

For networked sensor systems (NSSs) with hard and soft sensors including five uncertainties, two universal approaches of solving the robust fusion estimation problems are presented. It includes an integrated sequential covariance intersection (SCI) fusion minimax robust Kalman filtering approach with cross-covariance information and a generalized Lyapunov equation approach with four pairs of Lyapunov equations. Applying them, the robust local and SCI fused time-varying and steady-state Kalman filters are presented in the sense that their actual estimation error variances are guaranteed to have the corresponding minimal upper bounds. The equivalent batch SCI fusers are also presented. Their robustness and accuracy relations are proved, and the sensitivity of the SCI fuser with respect to the fused orders of sensors is analyzed. Applying the dynamic error system analysis method and the dynamic variance error system analysis method, a new convergence and absolute asymptotic stability theory of robust fusion Kalman filtering is presented. The classical Kalman filtering convergence and stability theory is developed. Compared with the original covariance intersection fuser, they significantly reduced the computational complexity and burden. Compared with the optimal and conservative SCI fusers, they significantly improved the robust accuracies. They are suitable to deal with asynchronous or random delayed data and are suitable for real-time applications. A simulation applied to the two-mass spring damper mechanical system shows their effectiveness.     

可见光与红外图像融合质量评价指标分析

目的 客观评价作为图像融合的重要研究领域,是评价融合算法性能的有力工具。目前,已有几十种不同类型的评价指标,但各应用领域包括可见光与红外图像融合,仍缺少统一的选择依据。为了方便比较不同融合算法性能,提出一种客观评价指标的通用分析方法并应用于可见光与红外图像融合。方法 将可见光与红外图像基准数据集中的客观评价指标分为两类,分别是基于融合图像的评价指标与基于源图像和融合图像的评价指标。采用Kendall相关系数分析融合指标间的相关性,聚类得到指标分组;采用Borda计数排序法统计算法的综合排序,分析单一指标排序和综合排序的相关性,得到一致性较高的指标集合;采用离散系数分析指标均值随不同算法的波动程度,选择充分体现不同算法间差异的指标;综合相关性分析、一致性分析及离散系数分析,总结具有代表性的建议指标集合。结果 在13对彩色可见光与红外和8对灰度可见光与红外两组图像源中,分别统计分析不同图像融合算法的客观评价数据,得到可见光与红外图像融合的建议指标集(标准差、边缘保持度),作为融合算法性能评估的重要参考。相较于现有方法,实验覆盖20种融合算法和13种客观评价指标,并且不依赖主观评价结果。结论...     

小目标检测研究综述

随着计算机视觉和人工智能技术的快速发展,目标检测受到了更加广泛的关注。由于小目标像素占比小、语义信息少、易受复杂场景干扰以及易聚集遮挡等问题,导致小目标检测一直是目标检测领域中的一大难点。目前,视觉的小目标检测在生活的各个领域中日益重要。为了进一步促进小目标检测的发展,提高小目标检测的精度与速度,优化其算法模型,本文针对小目标检测中存在的问题,梳理了国内外研究现状及成果。首先,分别从小目标可视化特征、目标分布情况和检测环境等角度对小目标检测的难点进行了分析,同时从数据增强、超分辨率、多尺度特征融合、上下文语义信息、锚框机制、注意力机制以及特定的检测场景等方面系统总结了小目标检测方法,并整理了在框架结构、损失函数、预测和匹配机制等方面发展的较为成熟的单阶段小目标检测方法。其次,本文对小目标检测的评价指标以及可用于小目标检测的各类数据集进行了详细介绍,并针对部分经典的小目标检测方法在MSCOCO(Microsoft common objects in context)、VisDrone2021(vision meets drones2021)和Tsinghua-Tencent100K等数据...     

Circularly polarized patch antenna with simultaneously wide frequency tuning range and high gain performance

A tunable circularly polarized square patch antenna with parasitic elements is designed for a wide frequency tuning range and high gain characteristics. The proposed antenna is constructed by one main patch and four semi-elliptic parasitic units. By loading four varactor diodes and adjusting their capacitance values, the tunable feature is performed to reallocate the corresponding working frequency. Moreover, the diagonal corners of the antenna are cut and loaded with varactor diodes, which provide the appropriate perturbation between the two orthogonality modes of the antenna, so as to ensure the circular polarization characteristic in the entire operating tuning band. The experimental results demonstrate that the reflection coefficient and axial ratio are less than −13 dB and 3 dB, respectively. The proposed antenna features a relatively wide continuously tuning range of 24% within 1.9-2.3 GHz and a stable gain of over 7 dBi with a radiation efficiency of above 85%.     

采用阶梯 T 型谐振器的双陷波 UWB 滤波器

为有效抑制印度国家卫星通信C频段和X卫星频段对超宽带通信系统的干扰,提出了一种新型双陷波超宽带滤波器。该滤波器采用阶梯T型多模谐振器(multimode resonator, MMR)与缺陷地结构(defected ground structure, DGS)的交趾耦合,实现超宽带特性。采用非对称耦合线及在MMR两侧耦合分裂环谐振器的方法,分别在6.67～7.06 GHz, 7.47～7.57 GHz两个频段内产生陷波。实测结果与仿真结果吻合较好,该滤波器的通带范围为3.03～11.50 GHz, 3 dB带宽达到123%,插入损耗仅有0.87 dB,两处陷波中心频率分别在6.87 GHz和7.52 GHz,陷波深度均大于20 dB,且整体尺寸紧凑,仅有16 mm×8 mm大小。     

基于直线检测和数字地图匹配的车辆航向角估计

为减少车辆行驶过程中由于卫星信号失锁及惯导累计误差对航向角的影响,结合场景特征的提取、表达和数字地图信息,提出了一种基于直线检测和数字地图匹配的车辆航向角估计方法。首先,根据地图匹配的坐标点计算车道线地图对应点的方位角,计算车辆航向角与车道线方位角的角度差;其次,通过改进的FLD直线检测方法识别并计算道路图像中车道线直线的角度;将双侧车道线直线角度作为BP神经网络的输入,以预测角度差作为网络输出;最后,结合预测角度差和车道线方位角得到实时车辆航向角。经实验验证,所提方法的航向角估计精度与现有估计方法及普通传感器测量结果相比具有一定的优势。     

基于 GRU-UKF 的锂离子电池 SOC 估计方法研究

精确估计锂离子电池荷电状态(SOC)是电池管理系统的关键技术之一,直接影响着动力锂电池组的使用效率和安全 性。 锂离子电池特性复杂,其 SOC 无法直接测量,且受电流、温度等因素的影响较大。 为此,提出了一种基于门控循环单元 (GRU)神经网络与无迹卡尔曼滤波(UKF)相结合的组合算法。 该方法利用 GRU 网络获得可测量的电流、电压、温度与锂电池 SOC 之间的非线性关系,并以此作为 UKF 的观测方程。 然后,通过 UKF 估计 SOC 值以提高算法的估计精度。 实验结果表明, 在不同温度以及不同的工况下,本文所提方法的均方根误差(RMSE)和平均绝对误差(MAE)分别小于 0. 51%和 0. 46%,均能提 高 SOC 的估计精度。     

中央空调传感器双重降噪模糊故障检测方法

针对现有降噪方法存在噪声残留以及异常检测指标受噪声影响较大的问题,提出中央空调传感器双重降噪和模糊指标 的故障检测方法。 自适应噪声的完整经验模态分解(complete EEMD with adaptive noise,CEEMDAN)所具有的噪声残余等问题, 用局部均值估计提取 k 阶模态替换模态估计完成初次降噪;而早期出现的虚假模式,先通过相关系数准则筛选含噪分量尽可能 保留有效信息,然后计算奇异值差分谱确定降噪阶次进行奇异值分解(singular value decomposition,SVD)完成二次降噪。 最后, 结合能量和峭度系数提出模糊指标作为异常信号控制限进行故障检测。 采用中央空调实验系统运行数据对所提方法进行验 证,结果表明,该方法具有良好的降噪及敏感特征筛选能力,信噪比提升 20. 203 7 dB,均方误差平均减小 48. 75%,故障检测准 确率平均提升 8. 67%,响应速度提升 33. 3%,抗噪性及检测效果提升明显。