有源相控阵可靠性分析及设计

基于有源相控阵原理和特点,对有源相控阵可靠性特征展开了分析。在同等复杂度下,采用可靠性表决模型和全串联模型对可靠性特征进行了对比分析,给出了有源相控阵表决模型设计的工程经验参数,并利用氮化镓器件对有源相控阵高可靠性设计进行了展望。     

基于斜投影算子的引信抗主瓣干扰方法

目的 利用信号极化域信息滤除干扰信号,解决回波阵列期望信号和主瓣干扰信号的入射角一致导致空域滤波抗干扰失效的问题。方法 由于主瓣干扰信号的极化状态通常是未知的,为此提出基于斜投影的抗主瓣干扰方法。该方法利用极化域–空域联合谱多信号分类算法,估计主瓣干扰信号的极化状态。然后,利用期望信号和主瓣干扰信号极化状态的差异,通过构造斜投影算子,处理阵列接收数据,从而滤除主瓣干扰信号。结果 当主瓣干扰导向矢量失配,或者期望信号与主瓣干扰信号的极化状态满足一定程度的差异时,基于斜投影的抗主瓣干扰方法均取得良好效果。结论 基于斜投影的抗主瓣干扰方法具有稳定性好、鲁棒性强等优点,可应用于雷达、无线电引信等系统对主瓣干扰的抑制,提升雷达、无线电引信等系统适应复杂电磁环境的能力。     

一种可同时检测挥发性氯代烷烃和氯代烯烃的电子鼻的研制

开发了一种可用于快速检测挥发性氯代烷烃和氯代烯烃气体的电子鼻系统.该电子鼻系统的核心检测部件为3个金属氧化锡传感器及一个光离子化传感器(PID)所构成的传感器阵列.基于对9类单一成分标准气体和5类混合标准气体的测试分析建立了气体类型识别模型,然后通过加标实验与气相色谱法比较验证了电子鼻系统检测的有效性.结果表明:①电子鼻中各传感器对氯代烯烃和氯代烷烃的响应有差异.PID对氯代烷烃无响应,对氯代烯烃有线性响应(R2>0.997).传感器TGS2602对四氯化碳(CT)、三氯甲烷(TCM)和1,2-二氯乙烷(1,2-DCA)较为灵敏,对前两者的定量性较好,但对1,2-DCA的线性响应很差.传感器TGS2600和TGS2620对二氯甲烷(DCM)和1,2-DCA较为灵敏,且线性响应程度好(R2>0.995).②建立了基于传感器阵列信号的气体类型简单识别模型:选用PID计算氯代烯烃浓度,TGS2602计算CT和TCM浓度,TGS2600或TGS2620计算DCM和1,2-DCA浓度.③TGS2602对标准混合气体的响应强度小于单物质响应强度之和,其它传感器对标准混合气体的响应强度接近于单物质响应强度之和.④电子鼻对污染水样中DCM和四氯乙烯(PCE)混合气体的检测结果与气相色谱分析值呈线性相关,相关系数R2>0.96.     

相控阵双波法缺陷定量与定性

介绍用相控阵超声检测（PAUT）,借助于缺陷衍射回波信号间距和波幅比,改善对缺陷进行定量定性的方法。缺陷快速定性（分类）和准确定量（测高）对在制检测和在用检测很有实用意义。期盼此法迅速推广应用于承压设备检测。     

The storage mechanism difference between amorphous and anatase as supercapacitors

Although TiO2 nanotubes is a promising electrode as supercapacitors due to its high energy density, easy synthesis and chemical stability, there are draw backs such as low conductivity and capacitance. Many studies concentrated on improving its electrochemical performance itself but little attention was payed to the reason of capacitance differences caused by its different crystal structures. Herein, we prepare amorphous and anatase TiO2 nanotubes and hydrogenated them by a simple electrochemical hydrogenation method to improve their conductivity and capacitance. And then study and compare their morphology and structure differences by SEM, TEM, XRD and BET. The results show that the pore size distribution, internal structure order and internal carrier concentration are the main reasons for their electrochemical performance differences. The microporous structure less than 2 nm in amorphous nanotubes act as a trap of electrolyte ions at current density larger than 0.1μA cm-2, leading to small charge and discharge capacitance. The long-range ordered crystal structure of anatase is more favorable for the orderly diffusion of carriers, reducing the inelastic scattering of carrier diffusion process and the electron hole-complexing probability, making anatase nanotubes exhibit higher coulomb efficiency and cycle stability than that of amorphous ones.     

基于声源成像的发动机模型试车噪声源分析

目的 在发动机试车噪声环境试验中,基于传声器阵列的声源成像测量方法,在近场单点测量之外,提供一种补充测量手段.方法 为验证基于传声器阵列的声源成像方法在发动机工作噪声试验研究中的有效性,通过发动机模型试车试验,设计并搭建传声器阵列,对试验噪声环境进行测量,并详细分析发动机试车中喷流噪声源特征.结果 通过声源成像分析手段获得了模型噪声源在时域和频域中的特征规律.通过声源成像云图中喷流噪声源在各个时刻的形态,能够直观反映出发动机模型工作各时刻状态.喷流噪声源在低频部分的能量比较高,声源主要分布在远离喷口的喷流下游位置处;在高频部分,声源主要分布在喷口附近.在中心频率为2000 Hz的1/3倍频程频段内,声压级最大的声源位置距离喷口最远.结论 通过试验和分析验证了声源成像在发动机模型试车噪声源分析中的可行性.     

Nonpolar cross-stacked super-aligned carbon nanotube membrane for efficient wastewater treatment

● A novel nonpolar super-aligned carbon nanotube (SACNT) membrane was prepared. ● SACNT membranes achieved smoother and more uniform structures. ● SACNT membranes have inert chemistry and unique nonpolar wetting feature. ● SACNT membranes exhibit superior separation and antifouling capabilities. ● SACNT membranes achieved superior oil/water separation efficiency. Membrane separation technology has made great progress in various practical applications, but the unsatisfactory separation performance of prevailing membrane materials hampers its further sustainable growth. This study proposed a novel nonpolar super-aligned carbon nanotube (SACNT) membrane, which was prepared with a layer-by-layer cross-stacking method. Through controlling the number of stacked SACNT layers, three kinds of SACNT membranes (SACNT_200, SACNT_300, and SACNT_400) were prepared. Systematic characterizations and filtration tests were performed to investigate their physico-chemical properties, surface wetting behavior, and filtration performance. Compared with two commercial membranes (Com_0.22 and Com_0.45), all the SACNT membranes achieved smoother and more uniform structures. Due to the hexagonal graphene structure of CNTs, the surface chemistry of the SACNT membranes is simple and inert, thereby potentially eliminating the covalent-bonding-induced membrane fouling. Besides, the SACNT membranes exhibited a typical nonpolar wetting behavior, with high contact angles for polar liquids (water: ~124.9°–126.5°; formamide: ~80.0°–83.9°) but low contact angles for nonpolar diiodomethane (~18.8°–20.9°). This unique nonpolar feature potentially leads to weak interactions with polar substances. Furthermore, compared with the commercial membranes, the SACNT membranes obtained a significantly higher selectivity while achieving a comparable or higher permeability (depending on the number of stacked layers). Moreover, the SACNT membranes exhibited superior separation performance in various application scenarios, including municipal wastewater treatment (> 2.3 times higher cleaning efficiency), electro-assistant fouling inhibition (or even self-cleaning), and oil/water separation (> 99.2 % of separation efficiency), suggesting promising application prospects in various fields.     

基于BP神经网络的污水格栅间气体监测

为实现对城市污水泵站格栅间内H₂S和CO有害气体浓度实时准确监测分析,设计气体传感器阵列监测系统,建立单隐层BP神经网络模型对气体浓度样本进行训练,确定网络隐含层数为9,训练函数为traindm,模型优化后输出的H₂S和CO气体浓度与实测值的平均相对误差分别为1.3%与0.4%。研究结果表明：采用BP神经网络模型对传感器阵列采集到的样本数据进行训练,可提高其测量精度,提升精度范围在57%～75%之间,能够满足对污水泵站有害气体监测的基本要求,所建立模型表现出良好效果。研究结果可为污水格栅间有害气体监测提供新方法。