装甲装备故障预测与健康管理系统技术研究

预测和健康状态管理(PHM)技术是一种先进测试、维修技术;从视情维修保障的背景出发,介绍了装甲装备PHM系统的内涵,进行了装甲装备故障模式影响和危害分析,明确了PHM系统具备的功能,初步构建了基于开放体系的装甲装备PHM系统的技术框架,并对其中的关健技术进行了深入研究,对炮控系统进行故障预测分析,结果和实际应用一致。     

STM32F207和DM9161A的以太网实现方案

电力抄表系统常通过网络采集和传输电网中的谐波等信息。本文提出了一种适合电力系统的网络设计方案。在STM32F207和DM9161A为核心的硬件平台上,完成了LwIP协议栈的移植,实现了远程终端和上位机通信。使电力系统更具实时性与交互性,并保证了通信的可靠性。     

数字化校园综合查询服务平台的设计与研究

本文在对数字化校园中心共享数据库及公共数据交换平台的研究基础之上设计了一种综合查询服务平台架构及查询服务功能,同时分析了查询实现过程。     

面向信息处理的突发事件语料库分类体系研究

本文分析了突发事件新闻的特点、建设突发事件新闻语料库的目的和意义,研究了突发事件新闻语料的分类体系和编码。研究结果对突发事件新闻语料库的建设、突发事件新闻信息检索、国家相关部门对突发事件应急处理方案制定以及对流行病学的医学研究等领域具有一定的理论意义和应用价值。     

Feature extraction using orthogonal discriminant local tangent space alignment

A novel algorithm called orthogonal discriminant local tangent space alignment (O-DLTSA) is proposed for supervised feature extraction. Derived from local tangent space alignment (LTSA), O-DLTSA not only inherits the advantages of LTSA which uses local tangent space as a representation of the local geometry so as to preserve the local structure, but also makes full use of class information and orthogonal subspace to improve discriminant power. The experimental results of applying O-DLTSA to standard face databases demonstrate the effectiveness of the proposed method.     

SVM-based ontology matching approach

There are a lot of heterogeneous ontologies in semantic web, and the task of ontology mapping is to find their semantic relationship. There are integrated methods that only simply combine the similarity values which are used in current multi-strategy ontology mapping. The semantic information is not included in them and a lot of manual intervention is also needed, so it leads to that some factual mapping relations are missed. Addressing this issue, the work presented in this paper puts forward an ontology matching approach, which uses multi-strategy mapping technique to carry on similarity iterative computation and explores both linguistic and structural similarity. Our approach takes different similarities into one whole, as a similarity cube. By cutting operation, similarity vectors are obtained, which form the similarity space, and by this way, mapping discovery can be converted into binary classification. Support vector machine (SVM) has good generalization ability and can obtain best compromise between complexity of model and learning capability when solving small samples and the nonlinear problem. Because of the said reason, we employ SVM in our approach. For making full use of the information of ontology, our implementation and experimental results used a common dataset to demonstrate the effectiveness of the mapping approach. It ensures the recall ration while improving the quality of mapping results.     

A critical review of the most popular types of neuro control

In this review article, the most popular types of neural network control systems are briefly introduced and their main features are reviewed. Neuro control systems are defined as control systems in which at least one artificial neural network (ANN) is directly involved in generating the control command. Initially, neural networks were mostly used to model system dynamics inversely to produce a control command which pushes the system towards a desired or reference value of the output (1989). At the next stage, neural networks were trained to track a reference model, and ANN model reference control appeared (1990). In that method, ANNs were used to extend the application of adaptive reference model control, which was a well‐known control technique. This attitude towards the extension of the application of well‐known control methods using ANNs was followed by the development of ANN model‐predictive (1991), ANN sliding mode (1994) and ANN feedback linearization (1995) techniques. As the first category of neuro controllers, inverse dynamics ANN controllers were frequently used to form a control system together with other controllers, but this attitude faded as other types of ANN control systems were developed. However, recently, this approach has been revived. In the last decade, control system designers started to use ANNs to compensate/cancel undesired or uncertain parts of systems' dynamics to facilitate the use of well‐known conventional control systems. The resultant control system usually includes two or three controllers. In this paper, applications of different ANN control systems are also addressed. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

RBF neural networks-based robust adaptive tracking control for switched uncertain nonlinear systems

In this paper, a robust adaptive H∞ control scheme is presented for a class of switched uncertain nonlinear systems. Radical basis function neural networks (RBF NNs) are employed to approximate unknown nonlinear functions and uncertain terms. A robust H∞ controller is designed to enhance robustness due to the existence of the compound disturbance which consists of approximation errors of the neural networks and external disturbance. Adaptive neural updated laws and switching signals are deducted from multiple Lyapunov function approach. It is proved that with the proposed control scheme, the resulting closed-loop switched system is robustly stable and uniformly ultimately bounded (UUB) such that good capabilities of tracking performance is attained and H∞ tracking error performance index is achieved. A practical example shows the effectiveness of the proposed control scheme.     

基于PR控制器的直接转矩控制策略研究

针对传统直接转矩控制中采用开关表控制造成转矩和电流脉动,以及传统调节器不能实现对交流输入信号的无静差控制等问题,基于电机空间电压矢量的转矩和磁链2个分量解耦的控制方式和PR控制器能够在静止坐标系下实现对交流输入信号的无静差控制,将PR控制器用于永磁同步电机的直接转矩控制中,并由此设计出磁链和转矩的双PR控制器。同时,在定子磁链的观测中,采用基于转子位置和定子电流的新型定子磁链估计方法。试验结果证明,将PR控制器对交流输入信号的无静差跟踪特性应用于基于空间电压矢量调制的直接转矩控制中,系统能获得优良的动态和静态响应,取得了显著的应用成效,由此验证了所提方法的正确性和可行性。     

混沌信号的主要测量特性分析

初步分析了混沌信号(以Logistic为例)应用于测量中的主要特性。仿真分析了Logistic信号的频谱特性、相关特性、模糊函数。说明了混沌信号在具有较高的距离速度分辨力,同时具备强抗干扰性。对比分析了混沌码和伪随机码的多普勒容限能力。初步分析Logistic信号的抗干扰特性。