基于多区域代理的分布式故障诊断方法

军用大型复杂装备组成涉及多个子系统或多个装备,故障诊断涉及上百个分散测试点数据采集和分离模块的诊断推理。传统装备采用集中测试和诊断方法,配套测试系统结构设计复杂、系统故障诊断算法效率低。本文基于D-矩阵故障诊断原理,提出基于多区域Agent的分布式故障诊断结构模型和区域Agent数据协同、区域Agent测试结果仲裁等问题的解决办法,并以某型舰船装备为例,验证了基于多区域代理的分布式故障诊断技术的有效性。     

A Ti3C2TX/Pt–Pd based amperometric biosensor for sensitive cancer biomarker detection

The detection of cancer biomarkers is of great significance for the early screening of cancer. Detecting the content of sarcosine in blood or urine has been considered to provide a basis for the diagnosis of prostate cancer. However, it still lacks simple, high-precision and wide-ranging sarcosine detection methods. In this work, a Ti₃C₂T_X/Pt–Pd nanocomposite with high stability and excellent electrochemical performance has been synthesized by a facile one-step alcohol reduction and then used on a glassy carbon electrode (GCE) with sarcosine oxidase (SO_x) to form a sarcosine biosensor (GCE/Ti₃C₂T_X/Pt–Pd/SO_x). The prominent electrocatalytic activity and biocompatibility of Ti₃C₂T_X/Pt–Pd enable the SO_x to be highly active and sensitive to sarcosine. Under the optimized conditions, the prepared biosensor has a wide linear detection range to sarcosine from 1 to 1000 µM with a low limit of detection of 0.16 µM (S/N = 3) and a sensitivity of 84.1 µA/mM cm². Besides, the reliable response in serum samples shows its potential in the early diagnosis of prostate cancer. More importantly, the successful construction and application of the amperometric biosensor based on Ti₃C₂T_X/Pt–Pd will provide a meaningful reference for detecting other cancer biomarkers.     

近红外二区活体荧光成像在肿瘤诊疗中的应用

由于具备组织穿透深度深和时空分辨率高等优势, 近年来近红外二区(Near-infrared-Ⅱ, NIR-Ⅱ, 1000~1700 nm)荧光成像技术得到了快速发展, 其在肿瘤临床诊断和治疗的潜力更是引发了广泛关注. 本文首先阐释了NIR-Ⅱ窗口荧光成像的原理及其优势, 随后根据结构分类归纳总结了现有荧光团的特征, 重点介绍了荧光探针在性能优化上的进展以及在肿瘤早期检测、 术中导航和光疗中的应用, 最后讨论了现有NIR-Ⅱ 荧光探针的局限以及临床转化面临的挑战, 并对未来的发展方向进行了展望.     

载酶纳米催化体系用于疾病诊疗的研究进展

酶作为一种具有高度特异性和高效性的催化剂, 可在细胞器中通过复杂有序的生化反应调节细胞的代谢过程. 受细胞区隔化结构的启发, 仿生设计纳米酶催化体系、 构筑限域酶催化微环境从而提高酶催化活性的研究为酶催化应用开辟了新思路. 纳米催化体系保留了小尺寸、 大比表面积、 肿瘤部位选择性富集等优势, 在疾病的诊疗方面发挥了巨大的优势. 本文首先总结了天然酶、 模拟酶和级联酶体系的催化机理, 对仿生构筑的纳米酶催化材料的载体体系进行了概述, 介绍了纳米酶催化体系在生物成像方面的应用, 讨论了其在相关代谢类疾病的作用途径, 并对纳米酶催化体系用于生物诊疗的发展前景进行了展望.     

Machine learning as an online diagnostic tool for proton exchange membrane fuel cells

Proton exchange membrane fuel cells are considered a promising power supply system with high efficiency and zero emissions. They typically work within a relatively narrow range of temperature and humidity to achieve optimal performance; however, this makes the system difficult to control, leading to faults and accelerated degradation. Two main approaches can be used for diagnosis, limited data input which provides an unintrusive, rapid but limited analysis, or advanced characterisation that provides a more accurate diagnosis but often requires invasive or slow measurements. To provide an accurate diagnosis with rapid data acquisition, machine learning methods have shown great potential. However, there is a broad approach to the diagnostic algorithms and signals used in the field. This article provides a critical view of the current approaches and suggests recommendations for future methodologies of machine learning in fuel cell diagnostic applications.     

真空中铝单丝电爆炸的实验研究

开展了铝单丝在负极性电流脉冲作用下电爆炸特性的研究.利用皮秒激光探针,搭建了阴影、纹影和干涉的光学诊断平台,得到了不镀膜铝丝典型的能量沉积过程,在电压崩溃时刻其沉积能量为2.4 eV/atom.为了增加金属丝内的沉积能量,开展了相同电参数及金属丝尺寸下的镀膜铝丝电爆炸实验,其沉积能量可达到5 eV/atom,实现了在电压崩溃之前铝丝完全气化(完全气化所需能量为4 eV/atom).阴影图像展示了高密度丝核区域的膨胀过程,不镀膜铝丝平均膨胀速度为2.2 km/s,而镀膜铝丝因为沉积能量大,其膨胀速度约为不镀膜铝丝的2.3倍,高密度区域膨胀速度为5 km/s.由于阴影不能反映低密度等离子体的膨胀,开展了平行双丝实验,通过测量自发光辐射,估算了低密度等离子体的膨胀速度.利用条纹相机拍摄了不镀膜铝丝电爆炸过程中自发光区域的图像.纹影图像清晰地展示了不镀膜铝丝在电爆炸过程中形成的核冕结构,而镀膜铝丝电爆炸过程中核冕结构得到了一定程度的抑制.从干涉图像计算了相移,在轴对称假设下对相移进行阿贝尔逆变换,重构了三维的铝原子数密度分布.     

Development of bioorthogonal SERS imaging probe in biological and biomedical applications

Living-cell imaging demands high specificity,sensitivity,and minimal background interference to the targets of interest.However,developing a desirable imaging probe that can possess all the above features is still challenging.The bioorthogonal surface-enhanced Raman scattering(SERS) imaging has been recently emerged through utilizing Raman reporters with characteristic peaks in Raman-silent region of cells(1800-2800 cm~(-1)),which opens a revolutionary avenue for living-cell imaging with multiplexing capability.In this review,we focus on the recent advances in the technology development and the biological and biomedical applications of the living-cell bioorthogonal SERS imaging technique.After introduction of fundamental principles for bioorthogonal tag or label,we present applications for visualization of various intracellular components and environment including proteins,nucleic acids,lipids,pH and hypoxia,even for cancer diagnosis in tissue samples.Then,various bioorthogonal SERS imaging-guided thera py strategies have been discussed such as photothera py and surge ry.In conclusion,this strategy has great potential to be a flexible and robust tool for visualization detection and diseases diagnosis.     

多值测试诊断策略优化设计

针对电子系统中多值测试条件下的测试排序问题,提出了一种诊断策略优化方法。首先,以相关性矩阵模型为基础,将已有的二值测试的优化算法同多值测试问题相结合,提出了适用于多值测试的基于霍夫曼编码的启发式函数;其次,将平均测试代价最小和平均测试步骤最少作为优化目标,采用与或树启发式搜索算法生成诊断树,得到多值测试的诊断策略,并给出了诊断策略优化方法的具体实现步骤;最后,将其应用到航空设备的实例中。结果表明提出的基于霍夫曼编码的与或树启发式搜索算法是可行的,其生成的诊断树是最优的,比基于信息熵的与或树启发式搜索算法具有更小的平均测试代价和更少的平均测试步骤。     

基于MDARM和VxWorks的小型无人机执行器故障检测方法

由于目前在小型无人机执行器故障诊断中存在着智能化程度较低,容易受到人为因素干扰,从而出现故障漏检等问题,难以满足小型无人机对飞行安全的要求。为此,本文提出一种基于多维数据关联规则挖掘(Multidimensional Data Association Rules Mining: MDARM)和VxWorks操作系统的小型无人机执行器故障诊断方法,通过建立执行器内部传感器测量的温度、压力、流速、力矩等相关变量的历史数据库,并对这些数据进行预处理,以避免带来噪声污染,并利用可测量参数与不可测量参数之间的关联性,建立故障诊断知识库,避免了诊断过程中的人为因素干扰,实现小型无人机执行器故障的精准测量。实验结果证明,这种方法能够有效地提高故障准确率64.7%,对小型无人机执行器的智能诊提供有效指导,应用前景广阔。     

基于遗传算法的自动驾驶仪测试性分析

为了提高自动驾驶仪故障测试与诊断的快速性与准确性,提出了一种基于遗传算法的自动驾驶仪测试性分析方法;此方法解决了遗传算法应用于测试项目选择的难点,构建了最优的故障测试策略,能以最短时间完成测试并满足测试覆盖性的要求;利用故障测试获得的知识,简化故障与测试间的相关性矩阵,加快了故障诊断的速度;最终获得了故障测试与诊断一体化的方法;实验结果表明,此方法有效提高了故障测试与诊断的速度,并且易于实现。