FTTH资源管理的研究与实现

随着PON技术的不断完善发展,FTTH逐渐成为运营商的主推宽带用户接入方案。ONT的数据配置比较’繁琐,且由于PON接入网络的无源性特点,给分光器的管理带来了一定困难。通过ONT的营业系统预配置,预先定义用户归属关系,可以解决ONT的配置问题和分光器的资源管理问题。     

炼钢MES计划调度一体化

阐述了计划层、执行层到控制层一体化,时间到空间一体化,时间和空间综合一体化,即计划调度"三个一体化"理念.针对炼钢MES计划调度的复杂性,提出了基于数据、知识、模型和人机协调的四维一体技术和方法.进而分析了一体化计划与调度协调框架多代理技术、基于区间多目标决策的工序组批建模技术、基于资源优化的计划模型协调技术等关键技术,对于实际应用具有一定指导意义.     

基于PRI谱的双门限雷达信号分选算法及其硬件平台设计

针对修正的PRI变换法无法分选重频参差雷达信号的缺点,提出了一种基于PRI谱的双门限雷达信号分选算法.该算法先对PRI谱设定双门限检测各个准PRI,再结合组合查看及序列搜索提取各个PRI.同时,构建了一种预分选、主分选结合的新型分选平台.预分选利用带有PowerPC的FPGA构架片上系统,完成对脉冲雷达信号的实时测量、AOA分类及数据存储;主分选采用DSP专职完成其他维参数的分选算法.谊分选新算法在保留抑制PRI子谐波优点的同时,对重频固定、抖动和参差的雷达脉冲信号都有较好的检测结果.视频信号源的大量测试表明,谊分选平台对普通雷达、PRI抖动和参差雷达、频率捷变雷达及一些特殊雷达均具有较好的分选能力.     

一种多模冗余结构存储器系统的容错设计研究

某型飞机代码转换器存储器用于存储ARINC419总线数据的地址,针对存储器数据易丢失影响数据传输的故障,提出了采用多模冗余结构的存储器系统容错设计方案;首先研究了三模冗余结构的可靠性,分析了存储器采用冗余结构设计的可行性,在此基础上,给出了多模冗余结构存储器实现方法和逻辑电路,并对其容错性进行了分析;实际工程应用表明,采用多模冗余结构存储器设计提高了国产化代码转换器的可靠性,降低了该设备的故障率。     

转子系统早期碰摩故障特征提取方法研究

航空发动机转子系统是发动机的核心部件,针对发动机转子系统早期碰摩故障难以检测的特点,通过对碰摩机理分析及早期故障特征的研究,提出了基于小波变换对原始信号降噪和虚拟仪器对转子系统振动数据采集相结合的方法,对转子系统早期碰摩故障特征进行提取,并在转子试验台上进行了实验验证。结果表明,采用LabVIEW程序采集转子系统振动数据并存储,然后应用小波变换进行数据分析和处理,能够对转子早期碰摩故障特征进行有效地提取。     

Intelligent Optimal-Setting Control for Grinding Circuits of Mineral Processing Process

During the operation of a grinding circuit (GC) in mineral processing plant the main purpose of control and optimal operation is to control the product quality index, namely the product particle size, into its technically desired ranges. Moreover, the grinding production rate needs to be maximized. However, due to the complex dynamic characteristics between the above two indices and the control loops, such control objectives are difficult to achieve using existing control methods. The complexity is reflected by the existence of process heavy nonlinearities, strong coupling and large time variations. As a result, the lower level loop control with human supervision is still widely used in practice. However, since the setpoints to the involved control loops cannot be accurately adjusted under the variations of the boundary conditions, the manual setpoints control cannot ensure that the actual production indices meet with technical requirements all the time. In this paper, an intelligent optimal-setting control (IOSC) approach is developed for a typical two-stage GC so as to optimize the production indices by auto-adjusting on line the setpoints of the control loops in response to the changes in boundary conditions. This IOSC approach integrates case-based reasoning (CBR) pre-setting controlling, neural network (NN)-based soft-sensor and fuzzy adjusting into one efficient control model. Although each control element is well known, their innovative combination can generate better and more reliable performance. Both industrial experiments and applications show the validity and effectiveness of the proposed IOSC approach and its bright application foreground in industrial processes with similar features.     

Properties of Cr:LiSrAIF(6) crystals for laser operation

We have performed several physical and optical measurements on the Cr:LiSAF (LiSrAlF(6)) laser material that are relevant to its laser performance, including thermal and mechanical properties, water durabilities, and Auger upconversion constants. The expansion coefficient, Young's modulus, fracture toughness, thermal conductivity, and heat capacity are all used to determine an overall thermomechanical figure of merit for the crystal. An investigation of the water durability suggests that the cooling solution should be maintained at pH = 7 to ameliorate problems associated with water dissolution. The Auger constant was found to become much more significant at higher Cr doping, in which excited-state migration leads to a substantial increase in the upconversion rate. We propose a design for a 50-W Cr:LiSAF laser system that is based on a detailed knowledge of all the relevant material parameters.     

In Situ Artificial Hybrid SEI Layer Enabled High-Performance Prelithiated SiOx Anode for Lithium-Ion Batteries

Considered the promising anode material for next-generation high-energy lithium-ion batteries, SiO_x has been slow to commercialize due to its low initial Coulombic efficiency (ICE) and unstable solid electrolyte interface (SEI) layer, which leads to reduced full-cell energy density, short cycling lives, and poor rate performance. Herein, a novel strategy is proposed to in situ construct an artificial hybrid SEI layer consisting of LiF and Li₃Sb on a prelithiated SiO_x anode via spontaneous chemical reaction with SbF₃. In addition to the increasing ICE (94.5%), the preformed artificial SEI layer with long-term cycle stability and enhanced Li⁺ transport capability enables a remarkable improvement in capacity retention and rate capability for modified SiO_x. Furthermore, the full cell using Li(Ni_0.8Co_0.1Mn_0.1)O₂ and a pre-treated anode exhibits high ICE (86.0%) and capacity retention (86.6%) after 100 cycles at 0.5 C. This study provides a fresh insight into how to obtain stable interface on a prelithiated SiO_x anode for high energy and long lifespan lithium-ion batteries.     

抑制图像非语义信息的通用后门防御策略

目的 后门攻击已成为目前卷积神经网络所面临的重要威胁。然而,当下的后门防御方法往往需要后门攻击和神经网络模型的一些先验知识,这限制了这些防御方法的应用场景。本文依托图像分类任务提出一种基于非语义信息抑制的后门防御方法,该方法不再需要相关的先验知识,只需要对网络的输入进行编解码处理就可以达到后门防御的目的。方法 核心思想是在保持图像语义不改变的同时,尽量削弱原始样本中与图像语义不相关的信息,以此抑制触发器。通过在待保护模型前添加一个即插即用的U型网络(即信息提纯网络)来实现对图像非语义信息的抑制。其输入是干净的初始样本,输出命名为强化样本。具体的训练过程中,首先用不同的训练超参数训练多个结构不一的干净分类器,然后在保持强化样本被上述分类器正确分类的前提下,优化信息提纯网络使强化样本和原始样本之间的差异尽可能地大。结果 实验在MNIST、CIFAR10和Image Net10数据集上进行。实验结果显示,经过信息提纯网络编解码后,干净样本的分类准确率略有下降,后门攻击成功率大幅降低,带有触发器的样本以接近干净样本的准确率被正确预测。结论 提出的非语义信息抑制防御方法能够在不需要相关先验知识的...     

Development,integration, and field evaluation of an autonomous citrus-harvesting robot

Citrus harvesting is a labor-intensive and time-intensive task. As the global population continues to age, labor costs are increasing dramatically. Therefore, the citrus-harvesting robot has attracted considerable attention from the business and academic communities. However, robotic harvesting in unstructured and natural citrus orchards remains a challenge. This study aims to address some challenges faced in commercializing citrus-harvesting robots. We present a fully integrated, autonomous, and innovative solution for citrus-harvesting robots to overcome the harvesting difficulties derived from the natural growth characteristics of citrus. This solution uses a fused simultaneous localization and mapping algorithm based on multiple sensors to perform high-precision localization and navigation for the robot in the field orchard. Besides, a novel visual method for estimating fruit poses is proposed to cope with the randomization of citrus growth orientations. Further, a new end-effector is designed to improve the success and conformity rate of citrus stem cutting. Finally, a fully autonomous harvesting robot system has been developed and integrated. Field evaluations showed that the robot could harvest citrus continuously with an overall success rate of 87.2% and an average picking time of 10.9 s/fruit. These efforts provide a solid foundation for the future commercialization of citrus-harvesting robots.