基于QPSO算法的支持向量机参数优化研究

应用具有量子行为的粒子群优化算法,对支持向量（SVM）进行参数优化研究．根据支持向量机的分类准确率和泛化能力之间的关系,应用QPSO算法选取比较优秀的参数模型,比较参数模型的各项性能,选取最适合实际需要的参数模型．仿真表明,QPSO算法的SVM模型与PSO算法相比在分类准确率和泛化能力上均获得更好的效果,经QPSO优化后的SVM整体性能明显提高．     

基于状态变换的数字电路冗余确认研究

以状态跳变图为基础,深入分析了冗余变换与非法变换的特征,提出结构冗余和功能冗余的概念,并讨论了可测故障、不可测故障和冗余之间的联系.最后结合验证和测试生成,提出状态冗余的隐含遍历确认策略.     

线膛火炮烧蚀弹道解法

以烧蚀火炮的阳线磨损曲线和一种挤进压力计算方法为基础 ,建立了考虑弹带挤进过程的内弹道模型。该模型可对不同磨损程度的火炮进行内弹道计算 ,能够较好地反映火炮内弹道性能随内膛磨损程度不同而变化的特征。     

Real-time prediction of projectile penetration to laminates by training machine learning models withfinite element solver as the trainer

Studies on ballistic penetration to laminates is complicated, but important for design effective protection of structures. Experimental means of study is expensive and can often be dangerous. Numerical simu-lation has been an excellent supplement, but the computation is time-consuming. Main aim of this thesis was to develop and test an effective tool for real-time prediction of projectile penetrations to laminates by training a neural network and a decision tree regression model. A large number of finite element models were developed;the residual velocities of projectiles fromfinite element simulations were used as the target data and processed to produce sufficient number of training samples. Study focused on steel 4340tpolyurea laminates with various configurations. Four different 3D shapes of the projectiles were modeled and used in the training. The trained neural network and decision tree model was tested using independently generated test samples using finite element models. The predicted projectile velocity values using the trained machine learning models are then compared with thefinite element simulation to verify the effectiveness of the models. Additionally, both models were trained using a published experimental data of projectile impacts to predict residual velocity of projectiles for the unseen samples. Performance of both the models was evaluated and compared. Models trained with Finite element simulation data samples were found capable to give more accurate predication, compared to the models trained with experimental data, becausefinite element modeling can generate much larger training set, and thus finite element solvers can serve as an excellent teacher. This study also showed that neural network model performs better with small experimental dataset compared to decision tree regression model.     

Numerical investigation of dynamic interaction with projectile and harmonic behaviour for T-finned machine gun barrels

Machine gun barrels differ from their rifle counterparts in terms of profile. To support high rates of sustained fire, machine gun barrels are made thicker in order to dissipate more heat and maintain their flexural rigidity and thus accuracy, but on other hand they also contribute in weight addition to weapon. This investigation deals with comparison between a conventional machine gun barrel and an improved innovative design having T-fins, both having same weight and chambered in 5.56 × 45 NATO ammunition, to compare their structural and harmonic characteristics which were parameterized by factors such as modal spectrum, directional deformation at muzzle ends during a single shot fire and harmonic behaviour at corresponding range of exciting frequencies. The solid models of both the barrels having same weight, were created using Solidworks. The continuous input data functions were generated by MATLAB using the field tested discreet data points. The generated velocity-distance functions were converted into time dependent functions using integration algorithms to calculate transient parameters such as time steps, excitation frequency range, angle of rotation of projectile and its angular velocity. The dynamic condition simulated the varying nature of forces due to eccentricity in projectile and this data was fed to a time step study using ANSYS transient structural work bench followed by modal and harmonic analysis. The results showed a significant reduction in muzzle end deformation which thus proved that the T-finned barrel, although had same weight as that of the conventional one, but had better structural and harmonic characteristics, and hence it would inherit better firing accuracy.     

舰用火炮对抗攻击过程的模拟与仿真

海上实兵环境下的舰炮对抗攻击训练,因发射实弹易造成误伤,一直被认为是难以实现的训练科目。而我系研制的舰炮对抗攻击模拟仿真系统,有效地将多种技术综合应用,创造了接近实战的训练环境;通过采用模拟交战的方法,较好地解决了上述问题。本文就该系统的组成结构、仿真过程与技术特点等问题进行了全面的介绍,并对模拟仿真训练系统的进一步发展提出了看法。     

机床颤振中“双频颤振”的研究

文中首次提出了机床颤振中“双频颤振”的论点,并对其产生机理进行了理论探讨且得实验验证。作者认为:对机床颤振中“双频颤振”进行研究不仅具有很重要的实用价值,而且将导致对现行的机床颤振理论的某些修改。     

几类基本学习认知模型

本文给出了几个类型的学习认知模型,并加以讨论     

枪械机构故障可靠性分析方法研究

介绍枪械机构组成、机构动作和作用,利用可靠性故障分析法中常用的FMECA分析法和FTA分析法对枪械机构产生的故障进行定性分析,并通过某典型自动步枪可靠性试验数据进行统计分析,找出枪械机构动作的主要故障,设计出FMECA分析表和FTA故障树．通过以上分析,提出一些对枪械机构的设计要求．     

枪械产品可靠性建模方法研究

选择适当的建模方法, 并在分析枪械产品可靠性试验特点的基础上提出了相应的假设, 讨论了确定具体模型类型的方法及不同类型数据的参数估计和检验手段。借鉴电子产品可靠性建模方法提出了针对枪械产品可靠性模型的建立步骤, 并结合某型自动步枪寿命试验数据给出计算实例。