层次分析法在多目标决策中的应用

由于定量型多目标决策的各指标值均为数量，因而按９度法建立各指标下的判断矩阵就很困难，限制了层次分析法在这一领域的运用，作者对此做了较深入的研究，认为层次分析法求解定量型多目标决策问题是可行的。为了便于构造判断阵，将决策中的所有指标分为正向指标、逆向指标和中心指标三类，同时给出了构造这三类指标的判断矩阵的方法，而且构造出来的判断矩阵自然满足一致性要求。给出的方法简单有效，并扩展了层次分析法的应用领域     

基于分级优化的飞机翼面结构布局综合技术研究

为了探讨飞机翼面结构主要纵横骨架的最佳布局问题．并提供符合工程实际的、用于概念设计阶段的飞机结构设计方法,本文采用分级优化与集成的策略,该策略分为三个层次。第一个层次为拓扑优化,并由此确定纵向骨架的个数与位置的最优布局;第二个层次为尺寸优化,它用来确定翼面的中间参数;第三个层次为稳定性准则优化,它确定横向骨架的个数与位置的最优布局。在分级优化的三个层次中,拓扑优化是独立的,尺寸优化与稳定性准则优化是相互耦合的。以国外某飞机机翼为例,结果表明本文提出分级优化的思路与所采用的集成方法是可行的,并且具有很好的数值效果。作者认为：它对从事飞机结构设计的人员有一定的指导性和参考价值,值得在飞机设计部门推广应用。最后,总结给出五点结论供参考。     

Topological Optimization Method for Aeronautical Thin-Walled Component Fixture Locating Layout

Fixture locating layout has a direct and influential impact on aeronautical thin-walled component(ATWC)manufacturing quality.The purpose is to develop a topological optimization method for ATWC fixture locating layout to minimize the manufacturing deformation.Firstly,a topological optimization model that takes the stiffness of ATWC as the objective function and the volume of the locating structure as the constraint is established.Secondly,ATWC and the locating structure are regarded as an integrated entity,and the variable-density method based topological optimization approach is adopted for the optimization of the locating structure using ABAQUS topology optimization module(ATOM).Thirdly,through a subsequent model reconstruction referring to the obtained topological structure,the optimal fixture locating layout is achieved.Finally,a case study is conducted to verify the proposed method and the comparison results with firefly algorithm(FA)coupled with finite element analysis(FEA)indicate that the number and positions of the locators for ATWC can be optimized simultaneously and successfully by the proposed topological optimization model.     

基于信息公理的车间布局问题评价方法

车间布局评价问题属于典型多属性决策问题.为了使信息公理更适合于解决多属性决策问题,通过增加满意度项改进了原有的信息量计算方法.属性值被划分为精确型、不确定型和模糊型,同时针对效益性、成本性、定值性和区间性属性给出了这三种数值类型的信息量的计算办法.改进后的信息量同时反映系统的成功概率以及决策者满意程度,并能够对包含多种数值类型的多属性决策问题进行评价.最后,作为实例,对焊接装配车间的布局方案进行了评价,结果验证了所改进的信息公理对于解决多属性决策问题的可行性和有效性.     

客机总体方案的综合评价方法

从民用飞机的经济性、环保性、舒适性和适应性出发,运用层次分析法建立多级层次结构,形成民机总体方案的综合竞争力评价模型。给出了民机方案各性能指标的量化方法,将设计准则转化为具体的民机性能指标。引入多人评价机制,提高评价模型各层级权重分布的合理性。应用本文方法对两种大型客机总体方案进行了综合评价,结果表明该方法能明确地识别出竞争力较高的设计方案,且评价结果具有合理性。算例表明该综合评价模型可用于民机总体方案的优选。     

基于TBIC信息准则的小波网络结构设计方法

针对框架小波网络存在的网络结构不易确定的问题．提出一种基于TBIC(Testing Bayesian information criterion)信息准则的网络结构设计方法。该方法权衡网络规模和测试精度两方面因素,得到了在TBIC信息准则下的最优小波网络,达到了优化网络结构的目的。仿真结果表明,用该方法设计得到的小波网络具有较小的网络结构和良好的测试精度。相比于BIC(Bayesian information criterion)准则函数,该准则能更准确地反映出测试精度随网络结构变化的趋势。     

基于模糊判断的产品方案综合决策方法研究

产品方案综合决策的主要任务是根据用户提出的功能要求从多个方案中选择实现该功能的最佳结构，这是一个复杂的多目标离散决策问题，层次分析法（Analytical hierarchy process,AHP)是解决这个问题的有效方法。本文在研究AHP产品决策方法的基础上，指出了传统模糊AHP算法具有依赖于判断矩阵的结构、计算复杂、不便于工程应用等局限性，提出在产品方案决策中用模糊特征向量法和区间判断的定量化方法来改进AHP算法，并以某企业专用齿轮箱产品设计方案为例证明了AHP改进算法的有效性。     

基于响应面方法的多目标有限元模型修正技术研究

研究基于响应面方法的多目标模型修正技术,并以一个实际结构为例进行修正。论述了该技术的主要步骤及其中参数选择、试验设计、响应面拟合、多目标优化和确认准则等关键技术的理论基础。设计结构并进行相关模态试验,用仿真软件MSC.Nastran建立该结构的有限元模型,然后基于该技术对模型进行修正。比较并分析试验结果与修正后仿真结果,通过两者前四阶频率与振型的比较,证明了该技术的有效性和合理性。     

Variational Mode Decomposition for Rotating Machinery Condition Monitoring Using Vibration Signals

The failure of rotating machinery applications has major time and cost effects on the industry.Condition monitoring helps to ensure safe operation and also avoids losses.The signal processing method is essential for ensuring both the efficiency and accuracy of the monitoring process.Variational mode decomposition(VMD)is a signal processing method which decomposes a non-stationary signal into sets of variational mode functions(VMFs)adaptively and non-recursively.The VMD method offers improved performance for the condition monitoring of rotating machinery applications.However,determining an accurate number of modes for the VMD method is still considered an open research problem.Therefore,a selection method for determining the number of modes for VMD is proposed by taking advantage of the similarities in concept between the original signal and VMF.Simulated signal and online gearbox vibration signals have been used to validate the performance of the proposed method.The statistical parameters of the signals are extracted from the original signals,VMFs and intrinsic mode functions(IMFs)and have been fed into machine learning algorithms to validate the performance of the VMD method.The results show that the features extracted from VMD are both superior and accurate for the monitoring of rotating machinery.Hence the proposed method offers a new approach for the condition monitoring of rotating machinery applications.     

基于证据理论的覆盖决策信息系统约简的数值刻画

决策为划分的覆盖决策信息系统的特征选择理论和方法日趋成熟。但在数据采集的过程中,有些数据集存在对象的决策缺失或决策不能完全确定情况,那么将决策刻画为覆盖更加合理。而决策为覆盖的覆盖决策信息系统特征选择的研究却很少见。本文讨论决策为覆盖的覆盖决策信息系统的特征选择,利用证据理论中的信任函数和似然函数给出覆盖决策信息系统约简的等价刻画,从而给出求约简的算法,并以实例说明该方法的有效性。     

动态神经网络的模型检验

讨论了利用仅含一个隐层的前馈多层神经网络来辨识离散时间非线性动态系统时的模型检验问题。从估计理论出发，加上实际应用的考虑，提出了一种检验神经网络模型适用性的综合误差指标（ＳＥＩ）准则，并利用学习速度快、收敛性能好的递推预测误差（ＲＰＥ）学习算法，对两个例子进行了仿真计算。结果表明：综合误差指标准则可用来检验非线性动态系统的神经网络模型。与相关检验法相比，综合误差指标准则具有计算简单、使用方便等优点。最后，指出了今后的研究方向。     

基于波束锐化技术的SAR图像增强方法

在对给定的合成孔径雷达图像进行增强处理时 ,遇到的主要问题就是相位信息的丢失和对成像系统参数的一无所知。本文将波束锐化技术与合成孔径辐射方向性图的估计相结合 ,为处理此类数据提高图像的视在分辨率提供了一种方法。该处理过程由一个优化的有限冲激响应滤波器构成。滤波器的设计思想基于最小均方误差准则 ,系数对称分布 ,系数取值决定于原图像中孤立强散射点的方位向响应 ,因为此响应可以被近似视为成像系统的合成孔径辐射方向性图。点目标仿真表明雷达角分辨率能够提高近 2倍。实测数据处理结果证明了该方法的有效性     

Threshold Selection Method Based on Reciprocal Gray Entropy and Artificial Bee Colony Optimization

Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class uniformity of gray level,a method of reciprocal gray entropy threshold selection is proposed based on two-dimensional（2-D）histogram region oblique division and artificial bee colony（ABC）optimization.Firstly,the definition of reciprocal gray entropy is introduced.Then on the basis of one-dimensional（1-D）method,2-D threshold selection criterion function based on reciprocal gray entropy with histogram oblique division is derived.To accelerate the progress of searching the optimal threshold,the recently proposed ABC optimization algorithm is adopted.The proposed method not only avoids the undefined value points in Shannon entropy,but also achieves high accuracy and anti-noise performance due to reasonable 2-D histogram region division and the consideration of within-class uniformity of gray level.A large number of experimental results show that,compared with the maximum Shannon entropy method with 2-D histogram oblique division and the reciprocal entropy method with 2-D histogram oblique division based on niche chaotic mutation particle swarm optimization（NCPSO）,the proposed method can achieve better segmentation results and can satisfy the requirement of real-time processing.     

Cooperative Search of UAV Swarm Based on Ant Colony Optimization with Artificial Potential Field

An ant colony optimization with artificial potential field(ACOAPF)algorithm is proposed to solve the cooperative search mission planning problem of unmanned aerial vehicle(UAV) swarm. This algorithm adopts a distributed architecture where each UAV is considered as an ant and makes decision autonomously. At each decision step,the ants choose the next gird according to the state transition rule and update its own artificial potential field and pheromone map based on the current search results. Through iterations of this process,the cooperative search of UAV swarm for mission area is realized. The state transition rule is divided into two types. If the artificial potential force is larger than a threshold,the deterministic transition rule is adopted,otherwise a heuristic transition rule is used. The deterministic transition rule can ensure UAVs to avoid the threat or approach the target quickly. And the heuristics transition rule considering the pheromone and heuristic information ensures the continuous search of area with the goal of covering more unknown area and finding more targets. Finally,simulations are carried out to verify the effectiveness of the proposed ACOAPF algorithm for cooperative search mission of UAV swarm.     

卫星三维电缆网设计与制造一体化集成研究与应用

针对卫星三维电缆网数字化设计、制造协同"信息孤岛"问题,提出了卫星三维电缆网设计与制造一体化流程和方法。通过基于模型的定义（Model based definition,MBD）三维电缆网协同设计方法,可以快速生成标准化、精细化的三维电缆网。基于MBD三维电缆网设计与工艺联动,开发了电缆网设计、加工、检测和装配联动软件模块,形成了一套电缆模型工艺信息快速提取方法。通过具体型号应用,验证了该方法在电缆网设计、加工、检测和总装的有效性和精确性。     

基于拓扑优化技术的飞机普通框设计方法研究

为了能够合理地降低飞机结构重量系数,针对飞机结构件,以普通框为研究对象,通过对“敏度阈值”的改进,提出“敏度变阈值”概念,并与“约束补偿”策略结合而形成拓扑优化算法,用于普通框的材料布局设计。以一轻型飞机的后段某一普通框为例,拓扑优化结果表明：(1)等材料设计时,刚度提高百分之四十;(2）等刚度设计时,材料用量减少百分之三十。由此可以得出：(1)基于“敏度变阈值”的拓扑优化算法用于飞机普通框改进设计是可行的和有效的;(2)给出了一种具有可操作性的设计方法,用以实现框结构“等刚度”的设计思想;(3)所给出的方法易于飞机结构设计人员接受与掌握,并且具有工程实用价值。     

Wideband Signal Detection Based on MWC Discrete Compressed Sampling Structure

In order to solve the cross-channel signal problem caused by the uniform channelized wideband digital receiver when processing wideband signal and the problem that the sensitivity of the system greatly decreases when the bandwidth of wideband digital receiver increases,which both decrease the wideband radar signal detection performance,a new wideband digital receiver based on the modulated wideband converter(MWC)discrete compressed sampling structure and an energy detection method based on the new receiver are proposed.Firstly,the proposed receiver utilizes periodic pseudo-random sequences to mix wideband signals with baseband and other sub-bands.Then the mixed signals are low-pass filtered and downsampled to obtain the baseband compressed sampling data,which can increase the sensitivity of the system.Meanwhile,the cross-channel signal will all appear in any subbands,so the cross-channel signal problem can be solved easily by processing the baseband compressed sampling data.Secondly,we establish the signal detection model and formulate the criterion of the energy detection method.And we directly utilize the baseband compressed sampling data to carry out signal detection without signal reconstruction,which decreases the complexity of the algorithm and reduces the computational burden.Finally,simulation experiments demonstrate the effectiveness of the proposed receiver and show that the proposed signal detection method is effective in low signal-to-noise ratio(SNR)compared with the conventional energy detection and the probability of detection increases significantly when SNR increases.     

A REAL-VALUED GENETIC ALGORITHM FOR OPTIMIZATION PROBLEM WITH CONTINUOUS VARIABLES

提出一种用于连续变量函数优化的遗传算法。它由一种简单、适应面广的动态刻度适应值和选择算子、杂交与变异算子，以及这些算子相应的自适应概率组成。该算法经两个常用函数检验，并在图象识别的神经网络权值训练中得到应用。实验结果表明，该算法是一种快速有效的全局优化算法。     

基于在线学习RBF神经网络的故障预报

提出了一种基于在线学习神经网络的故障预报方法.该方法在网络设计过程中结合了"添加"准则和基于对网络输出贡献相对较小的"剪枝"准则."添加"过程中利用隐层的最大输出判断神经元的活跃性;"剪枝"过程中加入了滑动窗口,避免了误"剪枝".同时,调整过程只对输出响应比较大的神经元进行,大大减少了计算量,提高了实时性.仿真结果表明,利用该算法能够对一类带时变参数的非线性系统进行故障预报.     

防空态势评估系统分析及新型评估模型研究

态势评估是一个时敏、不确定的动态过程。为了正确评估态势、深刻认识评估过程,首先详尽分析了评估所需的18项威胁因子及其作用原理,利用高斯函数将数据模糊化并给出复杂威胁因子的贝叶斯推理模型。在此基础上提出一个优势互补的二级态势评估模型:远方目标未知信息较多时,依照关联规则假设重要未知信息,预测目标的威胁程度;信息完备时使用贝叶斯网络推理,具有更强的可信度。最后,实例仿真验证了该评估模型的正确性及合理性。