多源信息融合技术研究及应用

Multi-source Information Fusion Technology and Its Application

作者: 专业:信号与信息处理 导师:赵莲清 年度:2011 学位:硕士  院校: 华北电力大学(北京)

Keywords

information fution, Multi-source data, Neuro-fuzzy inference, Printing Control

        信息化建设是当前社会建设的重大课题,而多源信息融合技术是信息化建设中不可或缺的一门技术。本文是在这样的大背景以及依托高精密印刷综合控制检测系统项目下应运而生由于信息融合技术分为软件和硬件两部分,硬件主要表现在信息融合的结构和功能;软件主要表现在信息融合的一些算法。基于这样的思想,首先研究了信息融合的模型架构,比较和分析了各个模型结构的特点,在有硬件基础之上研究传统的卡尔曼滤波法,Bayes概率理论方法,D-S证据理论在信息融合中的应用。软硬件结构的研究为后续的复杂环境下信息融合的解决提供可靠的理论基础,在复杂环境下主要研究的内容有:分布式传感器检测,主要包括与,或,表决融合,在matlab环境下进行了实验仿真比较了三者之间的优劣;对于采集的奇异信号问题主要利用的是小波法和分形法,实验证明这两种方法对于奇异信号检测都有很好的效果;检测的奇异信号恢复问题,本文采用的是前后向线性预测法,达到恢复原始数据的目的;对于非线性非平稳的复杂环境下,现代信号处理技术,神经模糊推理理论方法建立的系统模型很好的体现了系统特性。在高精密印刷综合控制检测系统项目中,将数据融合的相关知识应用到具体实践中,主要表现在:1.压力传感器受环境温度的影响,利用LM算法的BP神经网络方法融合温度信息和压力信息,来减少温度特性对压力传感器的影响;2.利用神经模糊推理理论的相关知识融合温度和压力信息,精确控制电机推进的距离,以保证高质量地印刷。
    Information technology is an important role of social construction, and the multi-source information fusion is a key part of information technology. Based on the background and the help of the printing system project,this article came into being.The information fusion technology is divided into two parts:hardware and software. The hardware is mainly in the structure & function of information fusion and the software is mainly in the algorithms of the information fusion. Based on the theory, the information fusion model structures are compared and analysised.After that, a traditional Kalman filter,Bayes probability theory approach and D-S evidence theory in information fusion application are reseached. The reseach of the hardware and software structure provide a reliable theoretical basis for the subsequent fusion of the solution in a complex environment,which is shown as follows:the distributed sensor including’and’,’or’and ’voting fusion’, comparing the advantages and disadvantages between the three under the matlab environment; the wavelet and fractal methods are used for solving the acquisition of singular signal, which are proved that this singular signal detection for both methods have good results from the experiments;for the singular signal detection recovery problems, we use the forward and backward linear prediction method, to restore the original purpose of the data; for the nonlinear and nonstationary complex environments, the neural fuzzy inference system model theory method which is a kind of the modern signal processing, can accurately describe the system characteristics.During the integrated project of printing in high-precision control and measurement system, the data fusion-related knowledge are been into practice, which is mainly in:1. Pressure sensor affected by environmental temperature, which is used the LM algorithm of BP neural Networks integrated the temperature information and pressure information to reduce the influence of the temperature characteristic;2. With the help of the neuro-fuzzy inference knowledge of the theory,the temperature and pressure are merged, which can precisely control the distance of the motor forward to ensure high quality print.
        

多源信息融合技术研究及应用

摘要5-6
Abstract6
第1章 引言9-13
    1.1 选题背景及意义9-10
    1.2 信息融合技术概述10-12
        1.2.1 信息融合的理论由来11
        1.2.2 信息融合基本概念11
        1.2.3 信息融合发展概况11-12
    1.3 研究内容及论文组织结构12-13
第2章 多源信息融合的模型13-20
    2.1 信息融合的功能模型13
    2.2 信息融合结构模型13-19
        2.2.1 检测级融合模型14-15
        2.2.2 跟踪级融合结构15-17
        2.2.3 属性级融合结构模型17-19
    2.3 本章小结19-20
第3章 多源信息融合的基本算法及分析20-28
    3.1 基于卡尔曼滤波的数据融合20-22
    3.2 贝叶斯统计理论22-24
        3.2.1 Bayes公式22-23
        3.2.2 基于Bayes理论的数据融合23-24
    3.3 D-S证据理论24-27
        3.3.1 D-S证据理论基本概念24-25
        3.3.2 D-S证据理论的数据融合应用25-27
    3.4 本章小结27-28
第4章 复杂环境下的多源信息融合28-50
    4.1 复杂环境下分布式多传感器检测28-35
        4.1.1 多传感器系统的马尔科夫模型28-29
        4.1.2 分布式检测融合策略29-31
        4.1.3 仿真结果和分析31-35
    4.2 多传感器系统冲击干扰的预处理35-41
        4.2.1 奇异信号检测的分形法35-36
        4.2.2 奇异信号检测的小波法36
        4.2.3 抑制冲击信号的恢复36-39
        4.2.4 仿真结果和分析39-41
    4.3 信息融合的神经模糊推理理论方法41-49
        4.3.1 神经模糊推理理论的融合原理41-44
        4.3.2 神经模糊推理融合系统的结构44-49
    4.4 本章小结49-50
第5章 印刷控制系统中的信息融合技术50-63
    5.1 印刷综合控制系统传感器分布及检测结构50-51
    5.2 压力传感器检测原理及融合处理51-56
        5.2.1 检测原理51-52
        5.2.2 压力数据采集及融合处理52-56
    5.3 综合决策处理56-62
        5.3.1 综合系统结构及方案56-57
        5.3.2 数据融合的控制决策57-62
    5.4 本章小结62-63
第6章 总结和展望63-64
参考文献64-67
攻读硕士学位期间发表的论文及其它成果67-68
致谢68
        下载全文需58


本文地址:

上一篇:基于MSTP的老挝电力光传输网方案设计
下一篇:发电厂SCIS2008系统的改进与优化

分享到: 分享多源信息融合技术研究及应用到腾讯微博           收藏
评论排行