复杂钣金零件渐进成形方法

以复杂钣金零件－人面部模型零件为例,论述基于UG软件的建模及建模过程中应注意的问题、支撑模型的制作及其加工代码的生成、适用于渐进成形正成形过程的加工代码生成处理过程,给出加工代码的详细信息,成功加工出质量较高的人面部模型。人面部模型渐进成形试验结果表明,利用渐进成形正成形方法可以成形出形状复杂的钣金零件,生产小批量复杂零件可以节省时间与费用;UG生成的三轴数控加工代码需要通过处理才能应用于渐进成形正成形过程;复杂钣金件渐进成形过程中定位精度非常重要,定位精度高的零件厚度分布符合 的规律,并可以成功成形出设计的零件,定位精度误差较大时零件厚度分布不均匀,成形工具头与板 料的过度挤压侧板料厚度变薄急剧从而引起零件的过早破裂。     

一种基于网络密度分簇的移动信标辅助定位方法

现有移动信标辅助定位算法未充分利用网络节点分布信息,存在移动路径过长及信标利用率较低等问题。该文把网络节点分簇、增量定位与移动信标辅助相结合,提出了一种基于网络密度分簇的移动信标辅助定位算法(MBL(ndc))。该算法选择核心密度较大的节点作簇头,采用基于密度可达性的分簇机制把整个网络划分为多个簇内密度相等的簇,并联合使用基于遗传算法的簇头全局路径规划和基于正六边形的簇内局部路径规划方法,得到信标的优化移动路径。当簇头及附近节点完成定位后,升级为信标,采用增量定位方式参与网络其它节点的定位。仿真结果表明,该算法定位精度与基于HILBERT路径的移动信标辅助定位算法相当,而路径长度不到后者的50％。     

分离式双向凸起特征的双面数控渐进成形过程有限元分析

双向凸起特征是指沿Z轴正方向和负方向两个方向上都存在相互分离凸起形状的特征。双面数控渐进成形是一种采用两个同步运动成形工具头的新的全无模成形技术。利用有限元分析软件ANSYS/LS-DYNA分析了基于双面数控渐进成形技术的双向凸起特征的成形可能性。分析结果表明:利用双面数控渐进成形技术完全可以成形加工出分离式双向凸起特征。     

LexAGen: An interactive incremental scanner generator

This paper describes LexAGen, an interactive scanner generator which is the first component of an interactive compiler generation environment. LexAGen can generate fast scanners for languages whose tokens can be specified by regular grammars. However, LexAGen also supports several context-sensitive programming language constructs such as nested comments and the interaction between floating-point numbers and the range operator in Modula-2. In addition, LexAGen includes a fast new algorithm for keyword identification. However, the most important and novel aspects of LexAGen are that it constructs scanners incrementally and that specifications can be executed anytime for validation testing. LexAGen specifications are expressed and entered interactively in a restricted BNF format (no left recursion). All syntactic errors and token conflicts are detected and reported immediately as LexAGen incrementally constructs a deterministic finite automaton to represent the scanner. At any time, the user can test the scanner fragment which has been entered by supplying text to be scanned. Alternatively, the user can generate a C-code scanner from the automaton. The generated automaton uses a direct execution approach and is quite fast. LexAGen is implemented in Smalltalk-80. Its extensive use of interactive graphics makes it very easy to use. In addition, the object-oriented paradigm of Smalltalk-80 is the basis for the incremental analysis, the error detection scheme and an intermediate representation which can be easily modified to generate scanners in other target languages such as Pascal, Modula-2 and Ada.     

Incremental recursive descent parsing

The Recursive Descent method of parsing is well established in practice. An Incremental Parsing algorithm using the Recursive Descent method is presented. The algorithm is applicable to LL(1) grammars. The algorithm has been implemented for a subset of Pascal.     

Incremental generation of LR parsers

Implementation of a new compiler usually requires making frequent adjustments to grammar definitions. An incremental technique for updating the parser tables after a monor change to the grammer could potentially save much computational effort. More importantly, debugging a grammar is made easier if the grammar is re-checked for correctness after each small change to the grammar. The basic design philosophy of an incremental parser generator, and incremental algorithms for LR(0), SLR(1) and LALR(1) parser generation are discussed in this paper. Some of these algorithms have been incorporated into an implementation of an incremental LALR(1) parser generator.     

An Efficient Circle-Drawing Algorithm

An efficient incremental circledrawing algorithm which uses paired update of the decision variable is proposed. The output of the algorithm is identical to the output of Bresenham's algorithm but the total number of arithmetical operations is less. Efficiency of the algorithm is independent of the output devices. Its other advantages are discussed.     

Performance evaluation of power system stabilizers based on Population-Based Incremental Learning (PBIL) algorithm

This paper proposes a method of optimally tuning the parameters of power system stabilizers (PSSs) for a multi-machine power system using Population-Based Incremental Learning (PBIL). PBIL is a technique that combines aspects of GAs and competitive learning-based on Artificial Neural Network. The main features of PBIL are that it is simple, transparent, and robust with respect to problem representation. PBIL has no crossover operator, but works with a probability vector (PV). The probability vector is used to create better individuals through learning. Simulation results based on small and large disturbances show that overall, PBIL-PSS gives better performances than GA-PSS over the range of operating conditions considered.     

Low computational complexity family of affine projection algorithms over adaptive distributed incremental networks

This paper presents the problem of distributed estimation in an incremental network based on the family of affine projection (AP) adaptive algorithms. The distributed selective partial update normalized least mean squares (dSPU-NLMS), the distributed SPU-AP algorithm (dSPU-APA), the distributed selective regressor APA (dSR-APA), the distributed dynamic selection of APA (dDS-APA), dSPU-SR-APA and dSPU-DS-APA are introduced in a unified way. These algorithms have low computational complexity feature and close convergence speed to ordinary distributed adaptive algorithms. In dSPU-NLMS and dSPU-APA, the weight coefficients are partially updated at each node during the adaptation. In dSR-APA, the optimum number of input regressors is selected during the weight coefficients update. The dynamic selection of input regressors is used in dDS-APA. dSPU-SR-APA and dSPU-DS-APA combine SPU with SR and DS approaches. In these algorithms, the weight coefficients are partially updated and the input regressors are optimally/dynamically selected at every iteration for each node. In addition, a unified approach for mean-square performance analysis of each individual node is presented. This approach can be used to establish a performance analysis of classical distributed adaptive algorithms as well. The theoretical expressions for stability bounds, transient, and steady-state performance analysis of various distributed APAs are introduced. The validity of the theoretical results and the good performance of dAPAs are demonstrated by several computer simulations.     

一种改进INC和MPC的光伏最大功率点跟踪算法

最大功率点跟踪(MPPT)常用于在光伏发电系统中获取最大的功率输出。针对光伏系统最大功率点跟踪过程中存在动态响应速度和稳态跟踪精度难以兼顾的问题,提出了一种改进电导增量法(INC)结合模型预测控制算法(MPC)的光伏发电系统最大功率点跟踪技术。利用改进电导增量法获取光伏系统下一时刻的电流参考值,与模型预测控制器获取的电流值相比较,通过建立和评价系统两步长模型指标函数,达到MPPT快速跟踪的目的。仿真结果验证了该方法的有效性。