考虑连续性和对称性约束的复合材料风力机叶片纤维铺角优化

在复合材料结构的设计过程中,应考虑为满足结构性能和生产工艺要求所必需的制造性约束,使之贴合工程实际。论文基于复合材料层合板理论和离散材料优化方法,将铺层参数优化转换为离散多相材料的纤维铺角分布优化问题,构建了以结构柔顺度最小为目标函数,备选材料人工密度为设计变量,连续性约束和设计变量和等于1为约束函数的复合材料层合板分区细观纤维铺角优化数学模型。以考虑连续性与对称性约束的层合板和某风力机叶片进行应用,结果表明,考虑连续性和对称性约束的优化铺层方案可提高结构的性能,有效避免结构的翘曲变形,减小基体开裂的概率,更符合生产制造要求。

深层融合对称子空间学习稀疏特征提取模型

提出深层融合对称子空间学习稀疏特征提取模型.在深度子空间基础上,引入对称性、稀疏性约束,通过构建深层映射网络,完成深层特征提取.首先根据最小化重构误差准则构建基本子空间模型,并在构建过程中加入对称性、稀疏性约束.然后对基本子空间模型进行深度化改造,得到深层对称稀疏子空间模型.最后将各个层特征进行融合编码,得到深层特征提取结果.在人脸数据库及目标数据库上的实验表明,文中算法可以取得较高识别率及较好光照、表情、人脸朝向的鲁棒性.相比卷积神经网络等深度学习框架,文中算法具有结构简洁、收敛速度快等优点.

一类Takagi-Sugeno模糊控制器的自适应遗传优化设计

提出了一类Takagi-Sugeno模糊控制器的自适应遗传优化设计方法。采用实数编码方式,并由自适应交叉和变异概率来控制遗传操作,有效地提高了参数优化的精度和算法的寻优效率。在优化过程中引入对称性参数约束条件,大大减小了算法的搜索空间。将该算法用于倒立摆T-S模糊控制器的设计,实现了控制器参数的快速自动整定。仿真结果表明,获得的T-S模糊控制器具有优良的性能。

Generalized Lutzky Conserved Quantities of Holonomic Systems with Remainder Coordinates Subjected to Unilateral Constraints

This paper focuses on studying the relation between a velocity-dependent symmetry and a generalized Lutzky conserved quantity for a holonomic system with remainder coordinates subjected to unilateral constraints. The differential equations of motion of the system are established, and the definition of Lie symmetry for the system is given. The conditions under which a Lie symmetry can directly lead up to a generalized Lutzky conserved quantity and the form of the new conserved quantity are obtained, and an example is given to illustrate the application of the results.

Mei Symmetry and Lutzky Conserved Quantity for Nonholonomic Mechanical System with Unilateral Constraints

In this paper, we study the Mei symmetry which can result in a Lutzky conserved quantity for nonholonomic mechanical system with unilateral constraints. The definition and the criterion of the Mei symmetry for the system are given. The necessary and sufficient condition under which the Mei symmetry is a Lie symmetry for the system is obtained. A Lutzky conserved quantity deduced from the Mei symmetry is gotten. An example is given to illustrate the application of our results.

Reconstruction of symmetric models composed of analytic curves and surfaces from point cloud

This paper presents a method to reconstruct symmetric geometric models from point cloud with inherent symmetric structure. Symmetry types commonly found in engineering parts, i.e., translational, reflectional and rotational symmetries are considered. The reconstruction problem is formulated as a constrained optimization, where the objective function is the sum of squared distances of points to the model, and constraints are enforced to keep geometric relationships in the model. First, the explicit representations of symmetric models are presented. Then, by using the concept of parameterized points (where the coor-dinate components are represented as functions rather than constants), the distances of points to symmetric models are deduced. With these distance functions, symmetry information, for both 2D and 3D models, is uniformly represented in the process of reconstruction. The constrained optimization problem is solved by a standard nonlinear optimization method. Owing to the explicit representation of symmetry information, the computational complexity of our method is reduced greatly. Finally, examples are given to demonstrate the application of the proposed method.

Unified Symmetry of Nonholonomic Mechanical Systems of Non-Chetaev＇s Type with Unilateral Constraints

The definition and the criterion for a unified symmetry of nonholonomic mechanical systems of non- Chetaev＇s type with unilateral constraints are presented based on the total time derivative along the trajectory of the system. A new conserved quantity, as well as the Noether conserved quantity and the Hojman conserved quantity, deduced froth the unified symmetry, is obtained. An example is given to illustrate the application of the results.

运动序列中动目标检测的稳健性方法

提出一种运动序列中动目标检测的稳健性方法。用尺度不变特征变换(SIFT)算法生成特征描述符,基于最近邻距离比(NNDR)进行初始匹配,增加对称性约束以获得稳健的匹配点集。随机抽样一致集算法(RANSAC)用于分离背景和目标对应特征点,实现背景运动的稳健性估计。背景补偿后,相邻帧差分和数学形态学方法实现动目标的分割。真实运动序列的实验结果表明,该算法能够获得稳健的匹配点对,检测出运动目标。

The Bargmann Symmetry Constraint and Binary Nonlinearization of the Super Dirac Systems

An explicit Bargmann symmetry constraint is computed and its associated binary nonlinearization of Lax pairs is carried out for the super Dirac systems. Under the obtained symmetry constraint, the n-th flow of the super Dirac hierarchy is decomposed into two super finite-diinensional integrable Hamiltonian systems, defined over the super- symmetry manifold R^4N{2N with the corresponding dynamical variables x and tn. The integrals of motion required for Liouville integrability are explicitly given.

Bargmann Symmetry Constraint for a Family of Liouville Integrable Differential-Difference Equations

A family of integrable differential-difference equations is derived from a new matrix spectral problem. The Hamiltonian forms of obtained differential-difference equations are constructed. The Liouville integrability for the obtained integrable family is proved. Then, Bargmann symmetry constraint of the obtained integrable family is presented by binary nonliearization method of Lax pairs and adjoint Lax pairs. Under this Bargmann symmetry constraints, an integrable symplectic map and a sequences of completely integrable finite-dimensional Hamiltonian systems in Liouville sense are worked out, and every integrable differential-difference equations in the obtained family is factored by the integrable symplectie map and a completely integrable tinite-dimensionai Hamiltonian system.