A novel combination belief rule base model for mechanical equipment fault diagnosis

Due to the excellent performance in complex systems modeling under small samples and uncertainty, Belief Rule Base(BRB) expert system has been widely applied in fault diagnosis. However, the fault diagnosis process for complex mechanical equipment normally needs multiple attributes, which can lead to the rule number explosion problem in BRB, and limit the efficiency and accuracy. To solve this problem, a novel Combination Belief Rule Base(C-BRB) model based on Directed Acyclic Graph(DAG) structu...     

Synthetic damage effect assessment through evidential reasoning approach and neural fuzzy inference: Application in ship target

The damage effect assessment of anti-ship missiles combines system science and weapon science, which can provide reference for the assessment of battlefield damage situation. In order to solve the difficulty of heterogeneous data aggregation and the difficulty in constructing the mapping between factors and damage effect, this paper analyzes the specific damage process of the anti-ship missile to the ship, and proposes a synthetic Evidential Reasoning (ER) – Adaptive Neural Fuzzy Inference System (ANFIS) to assess the damage effect. To solve the problem of fuzziness and uncertainty of criteria in the assessment process, the belief structure model is used to transform qualitative and quantitative information into a unified mathematical structure, and ER algorithm is used to fuse the information of lower-level criteria. In order to solve the problem of fuzziness and uncertainty of the information contained in the first-level variables, and the strong non-linear characteristics of the mapping between first-level variables and damage effect, the ANFIS with self-adaptation and self-learning is constructed. The map between the three first-level variables and damage effect is established, and the interaction process of the various factors in the damage effect assessment are clear. Sensitivity analysis shows that assessment model has good stability. The result analysis and comparative analysis show that the process proposed in this paper can effectively assess the damage effect of anti-ship missiles, and all criteria data are objective and comparable.     

Performance evaluation of complex systems using evidential reasoning approach with uncertain parameters

The composition of the modern aerospace system becomes more and more complex. The performance degradation of any device in the system may cause it difficult for the whole system to keep normal working states. Therefore, it is essential to evaluate the performance of complex aerospace systems. In this paper, the performance evaluation of complex aerospace systems is regarded as a Multi-Attribute Decision Analysis (MADA) problem. Based on the structure and working principle of the system, a new Evidential Reasoning (ER) based approach with uncertain parameters is proposed to construct a nonlinear optimization model to evaluate the system performance. In the model, the interval form is used to express the uncertainty, such as error in testing data and inaccuracy in expert knowledge. In order to analyze the subsystems that have a great impact on the performance of the system, the sensitivity analysis of the evaluation result is carried out, and the corresponding maintenance strategy is proposed. For a type of Inertial Measurement Unit (IMU) used in a rocket, the proposed method is employed to evaluate its performance. Then, the parameter sensitivity of the evaluation result is analyzed, and the main factors affecting the performance of IMU are obtained. Finally, the comparative study shows the effectiveness of the proposed method.     

人工智能在航天飞行任务规划中的应用研究

 在航天飞行任务中,如何设计航天器的飞行过程,如何确定地面对航天器的控制操作,如何制定飞行控制计划等,是地面飞行控制中心面临的重大问题,也是航天飞行任务规划所要解决的基本问题。在充分认识和把握人工智能基本原理、方法和技术的基础上,提出了一个基于规则演绎和状态演化的生长式推理模型,并对模型的特性进行了详细讨论,然后导出了该模型在航天飞行任务规划问题中的具体形式,从而成功地解决了航天任务自动规划的难题。通过在实际航天任务中的应用和验证,不仅证明该模型和方法是正确的、可行的和高效的,而且证明人工智能在航天飞行任务规划中有着广阔的应用前景。     

基于实例推理技术及其研究发展方向

基于实例的推理技术（Case- Based Reasoning ,CBR）是人工智能及机器学习领域中的前沿方向.作为一种增量式的学习方法,规避了传统人工智能在知识获取上的瓶颈问题.本文介绍了CBR的基本原理、实例中知识的表示方法和Tverskey和k-NN两种检索技术;详细讨论了CBR实现过程中的中心问题--实例修正问题,给出实例的修正的8种技术与方法;提出了基于实例的推理技术的研究重点和发展方向.     

航空发动机整机结构效率评估参数与计算方法

根据航空发动机整机结构系统功能和设计要求,对整机结构效率内涵进行了详细阐述,基于整机载荷特征,建立了从抗变形能力和力学环境适应能力两方面对整机进行结构效率评估的参数体系.通过对转静间隙变化量、应变能分布系数、敏感度系数等评估参数归一化方法及结构效率系数运算法则的建立,明确了结构效率的分析流程.以某小涵道比涡扇发动机为对象进行结构效率评估,详细给出了结构效率的计算过程.针对该小涵道比涡扇发动机的另一种结构方案2,基于结构效率评估方法进行评估并与原结构方案进行了对比分析,结果表明:原结构方案在抗变形能力和力学环境适应能力两方面均优于结构方案2,结构效率系数比结构方案2高出0.11,初步验证了结构效率评估方法的工程实用性.      

认知不确定性下可靠性灵敏度分析的新指标

传统的可靠性灵敏度指标只考虑了随机不确定性,当结构中还存在认知不确定性时,该指标难以反映出基本变量中认知不确定性对结构可靠性评估结果的影响程度.针对这一问题,引入概率包络来表达结构中的随机不确定性和认知不确定性,在此基础上建立了可靠性灵敏度分析的新指标——认知灵敏度系数,给出了其定义和代表的意义,并基于证据理论提出了认知灵敏度系数的计算方法.算例分析表明,认知灵敏度系数可以反映出基本变量中认知不确定性对结构可靠性评估结果的不确定性的影响程度,从而为有针对性地提高可靠性评估结果的准确性提供依据.另外,基于证据理论的认知灵敏度系数的计算方法适用于极限状态函数为单调、非单调的结构,以及变量服从正态、非正态的结构,具有普适性.     

Advanced multiple response surface method of sensitivity analysis for turbine blisk reliability with multi-physics coupling

To reasonably implement the reliability analysis and describe the significance of influencing parameters for the multi-failure modes of turbine blisk, advanced multiple response surface method(AMRSM) was proposed for multi-failure mode sensitivity analysis for reliability. The mathematical model of AMRSM was established and the basic principle of multi-failure mode sensitivity analysis for reliability with AMRSM was given. The important parameters of turbine blisk failures are obtained by the multi-failure mode sensitivity analysis of turbine blisk. Through the reliability sensitivity analyses of multiple failure modes(deformation, stress and strain) with the proposed method considering fluid–thermal–solid interaction, it is shown that the comprehensive reliability of turbine blisk is 0.9931 when the allowable deformation, stress and strain are3.7*10~(-3)m, 1.0023*10~9 Pa and 1.05*10~(-2)m/m, respectively; the main impact factors of turbine blisk failure are gas velocity, gas temperature and rotational speed. As demonstrated in the comparison of methods(Monte Carlo(MC) method, traditional response surface method(RSM), multiple response surface method(MRSM) and AMRSM), the proposed AMRSM improves computational efficiency with acceptable computational accuracy. The efforts of this study provide the AMRSM with high precision and efficiency for multi-failure mode reliability analysis, and offer a useful insight for the reliability optimization design of multi-failure mode structure.     

钛合金板材翻边成形的有限元数值模拟

在研究薄板冲压成形原理和模型描述的基础上,采用ANSYS有限元方法对钛合金板材翻边成形进行了系统的分析,完成对钛合金板材的室温和高温下的翻边成形过程的模拟,预测板材成形过程中的应变分布,并得出室温和高温下极限翻边系数,预测值与试验值相比较,拟合良好,同时应变分布规律符合试验结果,证明了有限元方法模拟钛合金热成形性的可行性和准确性。     

卫星动量轮灵敏性变异分析

基于模糊理论提出一种非线性卫星动量轮灵敏性变异分析的数值方法,以工程实际中的模糊相似关系转化为空间向量的模糊等价关系,来评估稳定系统的总体变异本质特征.并通过仿真均匀分布、线性分布以及周期分布的时间数据序列验证了该模型的可行性;以3套卫星动量轮实际稳态运转实验见证了该方法的实用性和有效性.其中动量轮A的最小灵敏系数为0.678,大于0.5阈值,表明其运转期间灵敏性十分良好;动量轮B的最小灵敏系数为0.439,小于0.5阈值,其运转期间灵敏性有所变异;动量轮C的最小灵敏系数等于0.5阈值,其关系最为模糊并介于稳定与变异之间.该模型实时预测并描述了动量轮灵敏性变异过程,且适用于诸多航天领域的非线性乏信息问题.      

定应变下固体火箭发动机药柱概率贮存寿命预估研究

为研究定应变对固体火箭发动机药柱概率贮存寿命的影响,对推进剂高温加速老化力学性能数据进行了统计分析,利用随机有限元法分析了发动机药柱在内压和过载的联合作用下Von Mises应变的均值和标准差,采用应力-强度干涉模型计算了药柱结构可靠性随应变敏感系数的变化趋势,据此分析了定应变对发动机药柱概率贮存寿命的影响。结果显示,定应变对发动机药柱概率贮存寿命影响显著,以0.97为可靠性下限,当应变敏感系数为2.94时,其寿命约为30.98年,应变敏感系数为-2.94时,其寿命约为0.92年,在此范围,药柱概率贮存寿命随应变敏感系数的增大而延长。     

案例推理和神经网络在航空发动机稳态模型中的应用

传统建模方法难以准确建立航空发动机数学模型,单纯使用BP神经网络建模又有其不足.将案例推理和改进BP方法相结合,根据案例推理优化训练数据,再利用神经网络,建立了发动机稳态模型.结果表明,该模型有较高的稳态精度,而且具有较好的泛化能力.     

基于弹道模型的磁测系统偏航干扰误差分析

常规弹丸在使用地磁算法测量滚转角的过程中,常将偏航角设为0°解算弹丸滚转角。当弹丸在飞行过程中偏航角发生变化时,滚转角解算精度受到一定影响。针对偏航角变化带来的误差与多种因素有关,且规律不清楚。在建立偏航角误差系数的基础上,使用Matlab软件建立了弹丸在不同偏航角、俯仰角、射向条件下的误差模型。首先建立了横风修正的质点弹道模型,通过蒙特卡罗方法仿真弹丸的轨迹分布,分析了弹载环境下磁测算法的滚转角误差,并验证了误差系数的准确性。通过仿真验证,误差系数可以较准确地表示滚转角误差与偏航角变化之间的关系,误差系数计算的误差与理论误差的差值小于10%,为后续实弹试验做好理论准备。     

基于VALOR NPI的航空电子模块DFM分析实现

为有效解决设计缺陷造成的航空电子模块可制造性问题,结合航空电子模块产品特点和工艺技术水平,提出建设基于VALOR的航空电子模块可制造性设计自动化设计平台,实现DFM自动化分析与设计,阐述了DFM设计的必要性、技术原理和实现过程,提出了“三库”构建方法和基于物料清单的印制电路板数据分析方法,应用结果表明,提出的方法能够覆盖PCB可制造性问题,提高分析效率。     

固体推进剂药柱不确定结构分析及方法比较

针对复合固体推进剂力学性能参数的不确定性对固体火箭发动机药柱结构分析的影响,使用软件ANSYS parametric design language(APDL)建立了受固化降温载荷和压力载荷联合作用下药柱结构的参数化有限元模型.在此基础上,分别应用蒙特卡洛法和响应面法,研究了复合固体推进剂热膨胀系数与初始泊松比的随机分布对药柱结构有限元分析的影响,并对两种方法得到的概率分析结果进行了对比.结果表明:复合推进剂热膨胀系数和初始泊松比微小的变化会对结构分析结果产生较大的影响;药柱结构响应对初始泊松比更为敏感.在药柱结构有限元分析时考虑推进剂力学性能参数的不确定性十分必要.通过对两种不确定结构分析方法的比较发现,响应面法得到的分析结果与蒙特卡洛法得到的分析结果十分接近,且分析效率远高于蒙特卡洛法.      

基于响应面插值的非线性气动弹性计算

飞翼、大展弦比低雷诺数气动布局容易在小迎角的条件下出现气流分离,会带来明显的非线性气动力问题,同时气动弹性带来的影响亦不可忽略。针对此类布局提出一种建立基于径向基函数插值的非线性压力系数分布模型的方法,利用径向基函数插值建立面元上压力系数对迎角导数的响应面,将压力系数积分并通过无限板样条(IPS)方法进行气动结构多次迭代插值实现非线性气弹分析。结果验证了该方法对于静气动弹性分析的有效性,同时能准确地反映弹性带来气动效率的降低和变形对升力及阻力的影响。     

An information-volume-based distance measure for decision-making

D-S evidence theory, as a general framework for reasoning with uncertainty, allows combining pieces of evidence from different information sources to derive a degree of belief function that is a type of fuzzy measure. However, the mass assignments given by unknown information sources are disordered. How to measure the difference between the mass assignments has aroused people’s interest. In this paper, inspired by the information volume, a novel distance-based measure is proposed to measure the difference between mass assignments. The method can refine the uncertain information given by experts and compare the refined information to obtain the difference between mass assignments. At the same time, it is verified that the measure not only meets the properties of distance, but also proves the superiority of the proposed Information Volume Distance (IVD) through simulation experiments. Meanwhile, in the process of information fusion, the reliability of each source could be quantified through IVD. Therefore, based on IVD, a new multi-source information algorithm is proposed to solve the problem of multi-source information fusion. Moreover, algorithm is applied to decision-making problem and compare with other methods to verify the effectiveness.     

神经网络模型在压气机通流特性分析中的应用

为了解决通流特性分析程序中原始模型对压气机性能预测精度不足的问题,提高压气机通流特性分析过程的可靠性,基于对大量多圆弧叶栅的数值模拟结果建立了压气机叶栅性能数据库,并以该数据库为依托,采用神经网络建模方法建立了压气机叶栅基准损失系数和基准落后角模型。结果显示:两模型对叶栅基准损失系数和基准落后角的预测精度均满足工程应用要求,其精度分别为±0.002和±1°。在对采用神经网络模型的通流特性分析程序校验过程中发现,其无论对压气机整机性能还是对流动细节的预测精度上都获得了显著提高,尤其是在主流区。此外从压气机整体特性上看,基准损失系数和基准落后角精度的提高对非设计工况损失系数和落后角的预测精度影响是积极的。      

基于熵与TOPSIS法的空中目标威胁判断

针对舰艇对空防御空中目标威胁判断指标属性权重与属性值均为区间数的情况,通过以各方案与理想方案偏差最小、与负理想方案偏差最大,以及权系数熵的最大化为优化目标,用拉格朗口乘子法给出模型的最优解,得到指标的权重值;基于区间数的4种不同的距离度量方式,建立基于TOPSIS法的威胁判断模型;通过实例对比在不同距离度量下的排序效果...     

民用飞机平尾载荷的不确定性及全局灵敏度分析

针对飞行载荷计算输入数据的随机不确定性会导致载荷计算结果波动的现象,采用Monte Carlo模拟方法和基于方差的全局灵敏度分析方法对民用飞机急剧俯仰机动随机平尾载荷进行不确定性及全局灵敏度分析。具体分析了飞机气动特性和重心的不确定性对迎角贡献平尾载荷、升降舵偏度贡献平尾载荷及平尾总载荷的影响,进一步通过全局灵敏度分析找出影响平尾载荷计算结果的主要因素。不确定性分析结果表明:气动特性和重心的不确定性导致迎角贡献平尾载荷的波动程度很大。灵敏度分析结果表明:1)升降舵偏度贡献平尾载荷只受升降舵效率的影响;2)迎角贡献平尾载荷主要受无尾飞机零迎角俯仰力矩系数和重心的影响;3)平尾总载荷受升降舵效率的影响最大,受无尾飞机零迎角俯仰力矩系数及重心的影响次之。此外也验证了方法的有效性,对提高飞行载荷的计算精度有一定的指导意义。