基于免疫FNN算法的加热炉炉温优化控制

针对复杂钢坯加热过程,提出了一种免疫克隆进化模糊神经网络(ICE-FNN)控制算法。首先根据现场样本数据建立过程神经网络模型;然后基于该模型,采用模糊神经网络控制器(FNNC)规则优化算法,确定FNNC的最佳规则数;最后由FNNC的规则优化所得参数构造初始种群的一个解,采用免疫克隆进化(ICE)算法对FNNC参数优化。该算法具有全局寻优和局部求精能力,仿真结果证实了其有效性。     

卫星任务调度问题的约束规划模型

卫星任务规划与调度是空间资源管理的重要内容之一,其目的在于为卫星系统的任务计划编制提供科学合理的决策手段与依据。卫星任务调度问题的重要特点在于,调度任务存在可见时间窗口约束。只有在可见时间窗口内,调度任务才可能执行并完成。在进行合理假设的基础上,建立卫星任务调度问题的约束规划模型。对基本禁忌搜索算法进行改进,提出了模型求解的变邻域禁忌搜索算法。应用结果表明,约束规划模型的建立与求解是合理的。     

大延时网络中的主动队列管理机制

研究了网络延时对路由器主动队列管理机制的影响,分析了几种典型主动队列管理算法在大延时网络中的性能。在介绍了基于内模补偿的DC-AQM算法的优缺点之后,根据PID控制器延时补偿的Ziegler-Nichols设定方法,提出了ZNDC(Ziegler-Nichols delay compensation)AQM算法并进行了仿真实验验证,实验结果表明算法达到了预期的目标。     

气囊辅助RTM制备复合材料承力筒内腔尺寸控制技术

根据气囊充压压力与复合材料承力筒内径之间的变化关系,给出了成型复合材料承力筒内表面的气囊尺寸计算方程。分析了气囊充压压力增大对承力筒的壁厚、纤维含量和弯曲性能的影响。采用气囊辅助RTM工艺整体制备出复合材料承力筒。试验结果表明,气囊充压压力使复合材料承力筒的壁厚减薄,纤维体积含量增加,弯曲性能提高;选择适当的气囊充压压力可以制备出满足设计要求的复合材料承力筒。     

Application of Markov renewal theory and semi-Markov decision processes in maintenance modeling and optimization of multi-unit systems

In this paper, a condition-based maintenance model for a multi-unit production system is proposed and analyzed using Markov renewal theory. The units of the system are subject to gradual deterioration, and the gradual deterioration process of each unit is described by a three-state continuous time homogeneous Markov chain with two working states and a failure state. The production rate of the system is influenced by the deterioration process and the demand is constant. The states of the units are observable through regular inspections and the decision to perform maintenance depends on the number of units in each state. The objective is to obtain the steady-state characteristics and the formula for the long-run average cost for the controlled system. The optimal policy is obtained using a dynamic programming algorithm. The result is validated using a semi-Markov decision process formulation and the policy iteration algorithm. Moreover, an analytical expression is obtained for the calculation of the mean time to initiate maintenance using the first passage time theory.     

OFDM系统中深度神经网络指导的IQ不平衡补偿算法

正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)是现代移动通信中一项重要的物理层通信技术,并且OFDM系统要求子载波间严格正交。然而,在实际系统中,振荡器和滤波器等器件的非理想特性会导致同相正交(In-phase and Quadrature-phase,IQ)不平衡,从而破坏子载波的正交性,严重影响OFDM系统的性能。通过研究IQ不平衡对OFDM系统的影响,提出了一种并联深度神经网络架构下的IQ不平衡补偿算法。该算法利用了深度神经网络不依赖于模型的特点,直接从接收到的频域信号恢复原输入信号的二进制序列,并利用干扰信号来自镜像子载波的先验知识来初始化模型驱动的神经网络,加快其网络优化的收敛速度。仿真结果表明,该算法能有效地补偿IQ不平衡失真,并且在幅度和相位失真的补偿上,其性能都优于传统的基于导频的最小二乘补偿算法,证明了深度学习方法解决物理层问题的优越性。     

Damage of multi-layer spaced metallic target plates impacted by radial layered PELE

Three different kinds of PELE (the penetrator with lateral efficiency) were launched by ballistic artillery to impact the multi-layer spaced metal target plates. The impact velocities of the projectiles were measured by the velocity measuring system. The damage degree and process of each layer of target plate impacted by the three kinds of projectiles were analyzed. The experimental results show that all the three kinds of projectiles have the effect of expanding holes on the multi-layer spaced metal target plates. For the normal structure PELE(without layered) with tungsten alloy jacket and the radial layered PELE with tungsten alloy jacket, the diameters of holes on the second layer of plates are 3.36 times and 3.76 times of the diameter of the projectile, respectively. For radial layered PELE with W/Zr-based amorphous composite jacket, due to the large number of tungsten wires dispersed after the impact, the diameter of the holes on the four-layer spaced plates can reach 2.4 times, 3.04 times, 5.36 times and 2.68 times of the diameter of the projectile. Besides, the normal structure PELE with tungsten alloy jacket and the radial layered PELE whit tungsten alloy jacket formed a large number of fragments impact marks on the third target plate. Although the number of fragments penetrating the third target plate is not as large as that of the normal structure PELE, the area of dispersion of fragments impact craters on the third target plate is larger by the radial layered PELE. The radial layered PELE with W/Zr-based amorphous composite jacket released a lot of heat energy due to the impact of the matrix material, and formed a large area of ablation marks on the last three target plates.     

Performance evaluation and optimization design of photoelectric pyrometer detection optical system

The measurement and control of high temperature play very important roles in national defense, military, scientific experiments, industrial and agricultural production. Photoelectric pyrometer is one of the important radiation thermometers for non-contact temperature measurement. It has an important application in the field of high temperature measurement, and its performance directly affects the accuracy of temperature measurement. By improving the design of the detection optical system of the photoelectric pyrometer, the imaging performance of the photoelectric pyrometer can be improved effectively, and the temperature measurement accuracy can be improved. In this paper, the temperature measurement principle of photoelectric pyrometer, the working principle of the detection optical system and the composition of the system are introduced. The optical components that affect the imaging of the optical system of the photoelectric pyrometer are analyzed. The optical pyrometer detection optical system is simulated by ZEMAX software, based on the analysis results, the Modulation Transfer Function (MTF) and the spot Diagram are used as the main evaluation criteria to optimize the design of the objective lens of the photoelectric pyrometer detection optical system. The imaging performance of the photoelectric pyrometer detection optical system and the accuracy of temperature measurement of the photoelectric pyrometer are improved by optimization design of the detection optical system.     

Theoretical and numerical investigations on the headspace of cartridge cases considering axial deformation and movement

The cartridge case headspace is the axial clearance between the cartridge and bolt of an automatic weapon, and influences the reliability and security of the weapon. Accordingly, theoretical and numerical studies were conducted to analyze the dynamic response of cartridge cases during internal impact considering the initial radial clearances between the cartridge case and chamber. A theoretical model was proposed to predict the cartridge case headspace considering both the deformation and movement of the cartridge case and confirmed by the results of nonlinear finite element simulations. The differences between the results of the conventional static model and the dynamic model were then comprehensively evaluated. The effects of the angle between the cartridge and chamber, the cartridge case material, and the internal impact pressure on the predicted headspace value were also analyzed. The dynamic response of the cartridge case predicted by the dynamic model was more accurate than that predicted by the conventional static model. The internal impact pressure, pressure change rate, and cartridge material were all found to affect the predicted headspace.     

Maximizing deviation method for multiple attribute decision making under q-rung orthopair fuzzy environment

Because of the uncertainty and subjectivity of decision makers in the complex decision-making environment, the evaluation information of alternatives given by decision makers is often fuzzy and uncertain. As a generalization of intuitionistic fuzzy set (IFSs) and Pythagoras fuzzy set (PFSs), q-rung orthopair fuzzy set (q-ROFS) is more suitable for expressing fuzzy and uncertain information. But, in actual multiple attribute decision making (MADM) problems, the weights of DMs and attributes are always completely unknown or partly known, to date, the maximizing deviation method is a good tool to deal with such issues. Thus, combine the q-ROFS and conventional maximizing deviation method, we will study the maximizing deviation method under q-ROFSs and q-RIVOFSs in this paper. Firstly, we briefly introduce the basic concept of q-rung orthopair fuzzy sets (q-ROFSs) and q-rung interval-valued orthopair fuzzy sets (q-RIVOFSs). Then, combine the maximizing deviation method with q-rung orthopair fuzzy information, we establish two new decision making models. On this basis, the proposed models are applied to MADM problems with q-rung orthopair fuzzy information. Compared with existing methods, the effectiveness and superiority of the new model are analyzed. This method can effectively solve the MADM problem whose decision information is represented by q-rung orthopair fuzzy numbers (q-ROFNs) and whose attributes are incomplete.