Virtual System of Signal Process Based on LabVIEW

传统的信号发生器只能产生正弦波、方波、三角波和锯齿波4种基本波形,而且体积庞大、接口不灵活、系统封闭、价格昂贵,针对这些缺点,本课题设计开发了一套基于虚拟仪器技术的信号的产生及数据处理系统,包括信号频谱分析及滤波。文中详细介绍了基于LabVIEW的信号处理系统的组建方法,重点阐述了用户界面及应用程序的设计。In contrast to the traditional signal generator which can only output the sine wave,the square wave,the triangle wave and the saw-tooth wave,which also has disadvantages of large volume,inflexible interface,closed system and high price,this paper designes a virtual instrument including function generator and fiter based on LabVIEW, which can not only have the basic profiles,but also offers three different kinds of filters

Electric Monitoring Sys tem Bas ed on USB Interface

中文摘要：为提升测量精度、 方便数据传输管理, 设计并实现了以 S3C44B0 处理器作为控制核心, CS5460 作为计量器件, 通过 USB 接口与上位机实现数据通讯的新型电能量测试系统; 重点讨论了 USB 接口程序的结构与实现。实践证明系统具有广 泛的适应范围。英文摘要：In order to make the electric moni tor sys tem have improved accuracy of measurement,convenient data transmis s ion,and convenient and friendly human- machine interface,this paper introduces a new electric moni tor sys tem which us es S3C44B0 as MCU,CS5460 as the chip of measure,and PDIUSBD12 as the chip of USB communication.It focus es on the s tructure and real ization of USB interface program.The practice shows that the sys tem has wide sphere of appl ication

Classification method of diabetes based on integration of characteristic classifier

目的:结合医用电子鼻技术,探讨糖尿病患者及其口腔呼气的气味图谱特征。方法:选择180例糖尿病患者和100例健康者,用医用电子鼻采集280例口腔呼气的气味图谱,采用基于数据特征划分的方法,用支持向量机和随机森林集成模型对糖尿病患者进行分类预测。结果:1线性核函数的支持向量机(SVM1)分类结果不是很理想,低于多项式核(SVM2)、径向基函数核(SVM3)和随机森林(RF)3种分类器,说明分类超平面显然是非线性的;2集成分类器对糖尿病患者和健康者的气味图谱特征的识别准确率可达88.04%。结论:基于特征划分的分类器集成方法预测性能明显好于单一分类器,为使用医用电子鼻进行糖尿病诊断分析提供了一种有效手段。Objective: To discuss the proi le features of oral odor of diabetic patients based on medical electronic nose technology. Methods: 180 patients of diabetes and 100 healthy people were selected, and the proi le features of oral odor of 280 volunteers were collected by using medical electronic nose. The classii cation forecasting was carried out on diabetic patients by using support vector machine(SVM) and random forest integration model based on partitioning method of data characteristics. Results: 1The classii cation result of SVM1 was not very good, which was lower than that of SVM2, SVM3 and RF, and the result showed that the classii cation hyperplane is nonlinear. 2The accurate rate of recognition of integrated classii er on diabetic patients and healthy people is 88.04%. Conclusion: The forecasting performance of classii er integration method based on feature division is superior to that of single classii er signii cantly, which provided an ef ective means for the diagnostic analysis of diabetes based on medical electronic nose.国家自然科学基金项目(No.81373552);; 福建省教育厅A类项目(No.JA14212);; 福建工程学院科研启动项目(No.GY-Z12079)~

Ship Motion Attitude Modeling and Prediction Based on Neural Network

舰船运动具有很强的随机性和非线性，直接影响着船上武备系统精度和舰载机安全着舰，因此对船舶运动姿态进行极短期预报研究具有重要的意义。神经网络具有非线性映射、自学习、自适应等优点，常被用于非线性系统的建模与预报；基于神经网络的融合应用技术已成为近年来船舶运动建模及预报的一个重要方向。本文将神经网络与非线性、灰色理论、粒子算法等相结合，提出了非线性回归模型和灰色神经网络组合模型；同时针对船舶运动的动态性，提出了带输出反馈的递归神经网络预测模型。论文的主要研究工作及创新成果如下： （1）本文用非线性自回归模型（NAR）来描述非线性的舰船运动。由于模型中非线性函数系数形式难以确定，本文用一组RBF网络...Ship motion is random and nonlinear, directly affects precision of ship weapon system and safety of carrier-based aircraft landing. So it is of great significance to do research on extreme short prediction of ship motion. Neural network is usually used for modeling and prediction of nonlinear system because of its nonlinear mapping, self-learning and adaptive characteristics. And the fusion techni...学位：工学博士院系专业：信息科学与技术学院自动化系_控制理论与控制工程学号：2322008015055

Second order Gray Neural Network in ship roll forecast

为了提高船舶的耐波性和适航性、对船舶横摇进行有效准确预报,提出了将灰色系统理论和神经网络进行有机结合的二阶灰色神经网络预报模型。介绍了二阶灰色预报模型,采用神经网络映射的办法构建灰色神经网络预报模型,并介绍了神经网络学习机制。另外,以某舰船横摇运动时间序列预报为例对模型进行仿真验证,有效改善了二阶灰色模型较大的预报偏差。仿真结果表明,gnnM(2,1)模型能准确预报船舶横摇运动,具有更高的预报精度和更好的数据稳定性。To enhance the ship’s seakeeping capacity and seaworthiness, a second order Gray Neural Network forecasting model is presented to forecast roll motion accurately.The gray system and its gray model are introduced, then using neural network mapping approach to build the second order GNNM(2, 1) model.On the other hand, the learning algorithm is presented.Further more, GNNM(2, 1) is applied in a sample of ship roll series and effectively improves large prediction error of second order gray model.The simulation results prove that the new model is more accurate and stable than tradition models.985工程学科建设项目(0000-x07204

Two Improved Model of GM(2,1) and Its Application in Ship Rolling Forecast

实时准确地预报船舶横摇运动是目前船舶运动研究的一个重要课题,对于提高船舶的耐波性和适航性具有重要的意义.灰色gM(2,1)模型有2个指数分量,能反映出序列摆动的运动情况,但预测精度仍然不足.因此在gM(2,1)模型对非线性复杂横摇运动进行建模及预测的基础上,基于误差补偿的思想,用周期外延和神经网络2种方法分别对灰色模型进行改进.仿真结果表明,灰色-周期外延组合预测模型和灰色-bP神经网络组合预测模型均能准确有效地预报船舶横摇运动,进一步提高灰色模型的预测精度,为船舶减摇控制打下了良好基础,具有实用价值.The study on forecasting rolling motion accurately is an important issue in shipping area.It is of great significance to enhance the ship′s seakeeping capacity and seaworthiness.Though GM(2,1) can model swing series,the accuracy is not high enough.In this paper,two improved model are proposed based on modeling and predicting on non-linear rolling motion by GM(2,1).The two combined model are gray cycle extension and gray neural network respectively based on error compensation.The simulation results illustrate both two methods can forecast rolling motion efficiently,and have higher accuracy,which lay good foundation for ship rolling stabilization.厦门大学985二期信息创新平台项目(0000-x07204

Methods of Sensor Placement for Fault Diagnosis

以系统的部件级物理结构或数学模型为对象,基于有向图技术提出了非线性系统满足故障可诊断性的传感器优化配置方法.在对有向图中故障检测与分离概念进行定义的基础上,设计了一种最小传感器配置方法,讨论了进一步优化的方法:1)按照实际配置情况,以价格、质量、体积与功耗混合的最小代价原则替代最小数量原则,给出了以最小配置为出发点的优化搜寻算法;2)考虑最小配置子集中某传感器发生故障导致的故障可诊断性功能缺失,设计了一种后补偿方法与一种直接补偿的改进贪婪算法.并以卫星的动量轮系统为例进行仿真,仿真结果验证了配置方法的有效性.Based on the directed graphs(DG),this paper investigates the method for optimizing the sensor configuration which can meet the fault diagnosability of nonlinear system described by component-level physical structure or a mathematical model.On one hand,agreedy algorithm satisfied failure detectability and separability is introduced particularly.Some discussions of the optimization method are made from two directions then.With the minimum configuration generated by the greedy algorithm as a starting point,a further searching algorithm in the principle of minimum cost which is considered as the hybrid of price,weight,volume and wastage makes the configuration of system sensors to be more realistic.On the other hand,in consideration of losses of failure diagnostic capability leaded by faulted sensor in minimum sensor configuration,this paper presents a compensated sensor configuration to all potential lost fault diagnostic functions and improves the greedy algorithm to achieve a direct compensation.Finally,the proposed approach is validated by using the momentum wheel system as an example.国家自然科学基金(61305117;61374037);; 国家重点实验室开放基金(9140c59030411ht05

preparationofacarbonnanotubeanalogfromsurfactantcontainingmcm41silica

A carbon nanotube analog was prepared using the structure-directing agent cetyltrimetylammonium bromide locked in the channels of MCM-41 as a carbon source. The structures and properties of the resulting samples were characterized by. powder XRD, nitrogen adsorption-desorption measurement, TEM and TGA. It was found that the carbon nanotube analog obtained by this method is amorphous. Pretreatment with concentrated sulfuric acid is a key step in its formation

preparationofacarbonnanotubeanalogfromsurfactantcontainingmcm41silica

A carbon nanotube analog was prepared using the structure-directing agent cetyltrimetylammonium bromide locked in the channels of MCM-41 as a carbon source. The structures and properties of the resulting samples were characterized by. powder XRD, nitrogen adsorption-desorption measurement, TEM and TGA. It was found that the carbon nanotube analog obtained by this method is amorphous. Pretreatment with concentrated sulfuric acid is a key step in its formation