基于新型多模态触觉传感器的机器人交互物体分类

多模态传感融合对于机器人探索外界环境十分重要,而现有的触觉传感器只能收集一种触觉模态信息,其收集到的多模态信息存在弱配对问题,为了解决此问题,研究了一种基于触觉和视觉融合的多模态触觉传感器。该传感器可以利用一个感知层同时收集2种异构触觉模态信息,弥补了传统触觉传感器的缺陷,同时可以利用收集到的多模态信息对不同物体的几何形状进行分类,在研究过程中,通过按压实验收集了圆形、正方形、长方形和三角形4种形状物体的触觉信息,再利用K最近邻(KNN)算法进行几何形状分类,实验结果证明了该传感器在区分不同物体的形状上具有良好的效果。     

LCL型并网逆变器临界无源阻尼参数设计

LCL滤波器因其良好的滤波性能被广泛应用于并网逆变器系统中。然而,LCL滤波器的固有谐振特性以及数字控制延时会严重危及系统稳定性。为提高系统鲁棒性,工程上通常采用无源阻尼方法以抑制滤波器谐振。由于滤波器谐振问题受多种因素影响,阻尼电阻的选取标准通常是模糊的。为准确、高效地设计阻尼电阻,文章结合阻尼电阻与滤波电容串联和与滤波电容并联两种典型无源阻尼方法,推导分析了“临界阻尼”指标。当系统阻尼大于临界阻尼时,LCL滤波器幅频特性曲线上的谐振峰被完全抑制,同时以最少的无源阻尼损耗为代价,充分保证了基于LCL滤波器的并网逆变器系统稳定性。此外,文章在PLECS软件中进行三相并网逆变器系统仿真,仿真结果验证了理论分析的有效性和正确性。     

四谱段TDICCD图像传感器的设计与制作

设计并研制了一种四谱段时间延迟积分电荷耦合器件(TDICCD)图像传感器,器件将四个TDICCD集成在同一芯片上,通过在光窗对应位置上镀不同的窄带滤光膜实现多谱段分光。该TDICCD图像传感器的像元尺寸为28μm×28μm,水平寄存器的有效像元数为3 072元,行频为10 kHz,电荷转移效率高达0.999 99,饱和输出电压为2 650 mV,抗弥散能力大于等于100倍,动态范围为7 143∶1。     

基于TDOA和SDOA的宽带辐射源双机无源定位算法

针对双无人机无源雷达对宽带辐射源目标的直接无源定位(DPD)初始值敏感,提出一种基于小生境拓扑结构改进矢量粒子群算法(NTVIPSO)的直接无源定位算法。本文算法将直接法和间接法结合起来,依靠间接法中尺度差参数构造约束条件,利用小生境矢量粒子群求解得到精确的位置。仿真结果表明本文粒子群算法优于矢量粒子群算法和邻域拓扑结构粒子群算法。提出的存在扰动情况下尺度差约束条件下的直接无源定算法精确度低于直接法,但优于间接法;计算复杂度低于直接法,大于间接法。     

Real time flood disaster monitoring based on energy efficient ensemble clustering mechanism in wireless sensor network

In this article, energy efficient ensemble clustering method (EECM) with black widow optimization (EECM-BWO) algorithm is proposed for effective data transmission with the help of real time flood disaster monitoring wireless sensor network (WSN). Initially, unified scalable ensemble clustering algorithm based on ensemble generation and consensus function is proposed for selecting the optimal routing path among the node using BWO algorithm. Then, biologically inspired routing black widow spiders optimization algorithm is proposed to trade off the nodes energy level, self-organization, and self-configuration in the WSN. The simulation is performed using NS2 simulator for validating the performance of the proposed EECM-BWO method. Here, in node, low delay achieves 24.07%, 72.58%, 51.36%, 81.75%, 77.74%, high packet delivery ratio achieves 70.83%, 53.93%, 90.23%, 43.58%, 24.58%, low packet drop attains 77.93%, 72.76%, 61.56%, 51.87%, 34.35%, low energy consumption attains 75.9%, 52.94%, 65.81%, 58%, 41.2% compared with existing energy-efficient clustering approach consolidated game theory as well as dual-cluster-head mode for WSNs energy-aware clustering by cuckoo optimization approach (EECM-COA), energy-aware clustering-based routing using multi-path reliable transmission with routing and control board (EECM-RCB-MRT), adaptive repair algorithm with temporally ordered routing algorithms for flood control strategy (EECM-AR-TORA-FCS), passive multi-hop clustering algorithm (EECM-PMC), dynamic source routing protocol based on genetic algorithm-bacterial foraging optimization (DSR-GA-BFO).     

基于宇称-时间对称光子晶体结构的磁场传感器研究

提出了一种基于宇称-时间(parity-time,PT) 对称结构的磁场检测微腔模型,利用水 基Fe₃O₄磁流体介质层的磁光效应和PT对称结构的光放大效应,当磁场强度发生变化时 ,引 起结构禁带中缺陷模位置的改变。因此,可以通过检测缺陷模位置实现磁场强度的检测。本 文利用传递矩阵法(transfer matrix method,TMM)从理论上分析了结构的透射光谱,在此 基础上对结构周期、介质层厚度、PT对称单元中宏观洛伦兹振荡强度等参数进行了数值优化 。优化后的仿真结果表明,该传感器能够实现有效的磁场磁强检测,磁场强度在0—500Oe 的 范围内,传感器的灵敏度可以达到97.14 nm/RIU,优值和检测极限分 别可以达到10⁴和10－7 RIU。同时, 传感器的分辨率数值最小可以达到0.05 Oe和最 大可以达到2Oe。本文所设计的传感器结构可用于高综合性能磁场强度检测设备的设计。     

A path planning model based on nested regular hexagons using weighted centroid localization

In many wireless sensor network (WSN) applications, the location of a sensor node is crucial for determining where the event or situation of interest occurred. Therefore, localization is one of the critical challenges in WSNs. Mobile anchor node assisted localization (MANAL) is one of the promising solutions for the localization of statically deployed sensors. The main problem in MANAL localization is that the path planning of the mobile anchor (MA) node should be done so that the localization error in the network will be minimal and that all unknown nodes in the network are covered. This paper proposes a new path planning approach called nested hexagons curves (NHexCurves) for MANAL. NHexCurves guarantees that it will receive messages from at least three non-collinear anchors to locate all unknown nodes in the network. The proposed model has compared six different path planning schemes in the literature using weighted centroid localization (WCL). In these comparisons, first of all, localization errors of the models are compared using some statistical concepts. Second, the variation of the localization error according to parameters such as resolution (R) and the standard deviation of noise (σ) is observed. Then, with similar approaches, the standard deviation of errors, localization ratio, scalability performances, and finally, path lengths of the models are examined. The simulation results show that the NHexCurves static path planning model proposed in this study stands out compared to other models with high localization error and localization ratio performance, especially at low resolutions, due to its path design. At the same time, the lowest error values according to σ are obtained with the proposed model among all models considered.     

Biodegradable Microparticles for Simultaneous Detection of Counterfeit and Deteriorated Edible Products

In an era of globalized trade relations where food and pharmaceutical products cross borders effortlessly, consumers face counterfeit and deteriorated products at elevated rates. This paper presents multifunctional, biodegradable hydrogel microparticles that can provide information on the authenticity and the potential deterioration of the tagged food or pharmaceutical formulations. These microparticles integrate spatially patterned authenticity code with two sensors—the first one detects possible presence of pathogenic microbes through monitoring pH while the second one identifies products stored above optimal temperatures via optical monitoring of the microparticle degradation. Particles are synthesized from a biocompatible polymer and a photoinitiator, dextran modified with 2‐hydroxyethylmethacrylate and riboflavin, respectively, using a continuous, high throughput method stop‐flow lithography. The proposed synthesis approach also enables crosslinking with visible light bringing about additional flexibility to flow lithography. Model liquid and solid food and pharmaceutical products are successfully labeled with microparticles and the functionality of the sensors in aqueous solutions is demonstrated.     

Gold immunochromatographic sensor for the rapid detection of twenty-six sulfonamides in foods

A gold immunochromatographic sensor (GICS) was developed for the rapid detection of 26 sulfonamides in honey samples.The sensor was based on a group-specific monoclonal antibody (mAb) that can recognize all 26 sulfonamides.Three haptens (hapten 1 with a thiazole ring,hapten 2 with a benzene ring,and hapten 3 with a straight carbon chain) were used for antigen preparation.With hybridoma technology,a group-specific mAb was screened with a 50％ maximal inhibitory concentration (IC50) against sulfathizole (STZ) and the other 25 analogues ranging from 0.08 to 90.18 ng/mL.Mono-dispersed gold nanoparticles were conjugated with the mAb to develop the lateral immunochromatographic strip.A labeled antibody concentration of 0.1 μg/mL and a coating antigen concentration of 0.2 μg/mL in the test line were chosen for strip preparation.Under optimized conditions,the visual limits of detection (vLOD) for the concentrations of STZ,sulfamethoxazole,sulfamethizole,sulfadiazine,sulfamerazine,sulfadimethoxine,sulfamonomethoxine,sulfameter,sulfamethoxypyridazine,and sulfachloropyridazine were 5,0.25,0.25,10,5,10,25,2.5,5,0.25,and 10 μg/kg,respectively.Scanner analysis in honey samples revealed good performance for detection of the 26 sulfonamides.Commercial honey samples were tested with the sensor and positive results were confirmed with high-performance liquid chromatography.The proposed strip sensor provides a convenient method for the rapid and reliable determination of sulfonamides pollutants in honey samples.     

Gold nanoparticle-based paper sensor for ultrasensitive and multiple detection of 32 (fluoro)quinolones by one monoclonal antibody

For rapid and simultaneous detection of (fluoro)quinolones, a broadly specific monoclonal antibody (mAb) that recognizes 32 (fluoro)quinolone antibiotics was prepared using a mixture of a norfloxacin derivative and a sarfloxacin derivative as the hapten. An immunochromatographic strip based on gold nanoparticles (AuNPs) was then assembled with goat anti-mouse antibody and antigen (sarfloxacin coupled to ovalbumin), used to form the C line and T line, respectively. This antigen competes with the (fluoro)quinolones in a sample incubated with mAbs labeled with AuNPs. The strip can detect 32 (fluoro)quinolones including oxolinic acid, nalidixic acid, miloxacin, pipemidic acid, piromidic acid, rosoxacin, cinoxacin, norfloxacin, pefloxacin, lomfloxacin, enofloxacin, fleroxacin, ciprofloxacin, enrofloxacin, dafloxacin, orbifloxacin, sparfloxacin, gemifloxacin, besifloxacin, balofloxacin, gatifloxacin, moxifloxacin, nadifloxacin, ofloxacin, marbofloxacin, flumequine, pazufloxacin, prulifloxacin, sarafloxacin, difloxacin, trovafloxacin, and tosufloxacin in milk within 10 min with the naked eye. The cut-off values of the strip range from 1 to 100 ng/mL and the limits of detection are 0.1–10 ng/mL. The strip does not cross-react with antibiotics including tetracycline, sulfamethazine, ampicillin, erythromycin, aflatoxin B1, or gentamicin. In short, this immunochromatographic strip is a very useful tool for the primary screening of (fluoro)quinolones in milk.

Open image in new window