多传感器数据融合研究

数据融合技术又称多传感器数据融合或分布式传感,即对多类多源和多平台传感器数据进行组合,提供有关空间信息综合态势的一种数据处理技术。数据融合可分为:信号级数据融合、像素级数据融合、特征级数据融合和符号级数据融合。本文讨论了红外图像、可见光图像、多谱图像、雷达图像等的数据融合问题以及各级数据融合的方法。     

多传感器管理研究及其应用

多传感器管理是在一个动态的、不确定性的环境中,管理和协调多个传感器集或多个测量设备,来提高数据融合的性能及对环境的检测程度.多传感器管理目的在于合理地优化传感器资源、对监测对象进行更好地控制.随着现代多传感器系统的发展,多传感器管理应用领域由军事领域逐步扩展到民用领域.本文介绍了多传感器管理的基本概念、结构、原理,分析了多传感器管理与信息融合之间的关系以及传感器管理中的几个主要问题及其相应的解决方法,指出目前多传感器管理研究中存在的问题及未来发展趋势.     

多传感器信息融合技术及其在智能材料结构中的应用

多传感器信息融合技术是对多传感器信号处理的一种有效方法，在军事和民用领域中有着广阔的应用前景，本文主要论述了多传感器信息融合技术的分类和多传感器信息融合技术的数据处理方法。并在此基础上，对多传感器信息融合技术在智能材料结构中的应用进行了研究。     

采用多传感器数据融合技术的消防报警系统

介绍了多传感器数据融合消防报警系统，然后在分析信号特征和各种算法的基础上提出数据融合的思想。根据多传感器的不同性质，进行多级别、多方面处理，以求更可靠更准确的结果。并提出了基于传感器数据融合的火灾报警的基本框架，最后讨论了传感器数据融合的方法和管理实施。     

基于模糊贴近度的多传感器数据融合测量

依据现代测量中多传感器数据融合需求,提出了一种基于模糊贴近度的数据融合新方法,研究了它在测量中的应用过程。测量应用实例验证了其在工程中的可行性,体现了稳定性、可靠性高的传感器在测量数据融合中的“优越性”,运算过程简洁、快速、有效,便于实时测量操作。     

基于多传感器信息融合的结构损伤识别研究

针对结构健康监测系统中的传感器数量多、数据信息复杂的特点，从模式识别和局部控制、全局参与的思想出发，提出了多传感器信息融合方法对结构损伤进行识别。首先应用小波包变换对结构振动测试数据进行特征提取，通过不同传感器特征向量的合成完成数据层融合；然后建立三个耦合神经网络分别实现结构损伤的确认、定位及定量，并完成决策层的信息融合；最后进行了36个损伤工况的结构模型实验研究，验证了所提出的方法是可行的和有效的。从实验验证的结果来看，对损伤率在7．5％以上的结构，损伤识别精度较高；对于损伤确认和损伤定位，识别精度较高，而对于损伤程度识别有一定偏差。     

数据融合在机械故障诊断中的应用研究

在机械故障诊断中引人了数据融合技术，并研究了多传感器数据融合的层次、模型。在实际的机械故障诊断应用中，使用了不同数据融合的层次和模型。对实例的分析表明，数据融合在机械设备故障诊断中是一种非常有效的方法，并有广阔的应用前景。     

基于分布式多子网神经网络的传感器静态误差修正

为消除温度等非目标参数对传感器输出特性的影响,本提出了一种采用多传感器数据融合技术的传感器静态误差修正新方法－传感器冗余法。该方法的显优点是系统不需测量非目标参数,通过对多种传感器输出数据融合达到消除非目标参数对传感器输出的影响,实现正确检测传感器的输入。同时本首次提出了一种新的神经网络结构：分布式多子网神经网络,并将其用于实现该修正方法。模拟实验表明,该网络在泛化能力、学习速度等方面均优于BP网络和RBF网络。其多子网、自动分解任务的特点尤其适用于复杂样本的学习,具有很好的应用前景。     

高光谱数据融合研究

多传感器的遥感数据融合在城市规划、土地利用、矿产探测、军事侦察等领域有着非常广泛的应用前景。本文高光谱图像光谱分辨率高、空间分辨率低、多光谱图像空间分辨率高、光谱分辨率高的特点,阐述了其数据融合。特别介绍了CRISP锐化算法。     

数据融合在测控技术中的应用

本文简单介绍了多传感器数据融合的有关知识 ,着重说明数据融合应用于测控技术中可以提高传感器及测控系统的性能。     

Multi-source data fusion study in scientometrics

This paper provides an introduction to multi-source data fusion (MSDF) and comprehensively overviews the ingredients and challenges of MSDF in scientometrics. As compared to the MSDF methods in the sensor and other fields, and considering the features of scientometrics, in this paper an application model and procedure of MSDF in scientometrics are proposed. The model and procedure can be divided into three parts: data type integration, fusion of data relations, and ensemble clustering. Furthermore, the fusion of data relations can be divided into cross-integration of multi-mode data and matrix fusion of multi-relational data. To obtain a clearer and deeper analysis of the MSDF model, this paper further focuses on the application of MSDF in topic identification based on text analysis of scientific literatures. This paper also discusses the application of MSDF for the exploration of scientific literatures. Finally, the most suitable MSDF methods for different situations are discussed.     

Multisensor fusion and integration: approaches, applications, andfuture research directions

Multisensor fusion and integration is a rapidly evolving research area and requires interdisciplinary knowledge in control theory, signal processing, artificial intelligence, probability and statistics, etc. The advantages gained through the use of redundant, complementary, or more timely information in a system can provide more reliable and accurate information. This paper provides an overview of current sensor technologies and describes the paradigm of multisensor fusion and integration as well as fusion techniques at different fusion levels. Applications of multisensor fusion in robotics, biomedical system, equipment monitoring, remote sensing, and transportation system are also discussed. Finally, future research directions of multisensor fusion technology including microsensors, smart sensors, and adaptive fusion techniques are presented     

The measurement of neutron and neutron induced photon spectra in fusion reactor related assemblies

The spectral neutron and photon fluence (or flux) measured outside and inside of assemblies related to fusion reactor constructions are basic quantities of fusion neutronics. The comparison of measured spectra with the results of MCNP neutron and photon transport calculations allows a crucial test of evaluated nuclear data as generally used in fusion applications to be carried out.The experiments concern mixed neutron/photon fields with about the same intensity of the two components. An NE-213 scintillation spectrometer, well described by response matrices for both neutrons and photons, is used as proton-recoil and Compton spectrometer. The experiments described here in more detail address the background problematic of two applications, an iron benchmark experiment with an ns-pulsed neutron source and a deep penetration mock-up experiment for the investigation of the ITER in-board shield system. The measured spectral neutron and photon fluences are compared with spectra calculated with the MCNP code on the basis of FENDL-1 data. The agreement is better than 10% except for the photon fluence from the iron benchmark experiment, which is underestimated in the calculations by 25%.     

Inverse wave field extrapolation: a different NDI approach to imaging defects

Nondestructive inspection (NDI) based on ultrasound is widely used. A relatively recent development for industrial applications is the use of ultrasonic array technology. Here, ultrasonic beams generated by array transducers are controlled by a computer. This makes the use of arrays more flexible than conventional single-element transducers. However, the inspection techniques have principally remained unchanged. As a consequence, the properties of these techniques, as far as characterization and sizing are concerned, have not improved. For further improvement, in this paper we apply imaging theory developed for seismic exploration of oil and gas fields on the NDI application. Synthetic data obtained from finite difference simulations is used to illustrate the principle of imaging. Measured data is obtained with a 64-element linear array (4 MHz) on a 20-mm thick steel block with a bore hole to illustrate the imaging approach. Furthermore, three examples of real data are presented, representing a lack of fusion defect, a surface breaking crack, and porosity.     

Smart-City-based Data Fusion Algorithm for Internet of Things

Increasingly, Wireless Sensor Networks (WSNs) are contributing enormous amounts of data. Since the recent deployments of wireless sensor networks in Smart City infrastructures, significant volumes of data have been produced every day in several domains ranging from the environment to the healthcare system to transportation. Using wireless sensor nodes, a Smart City environment may now be shown for the benefit of residents. The Smart City delivers intelligent infrastructure and a stimulating environment to citizens of the Smart Society, including the elderly and others. Weak, Quality of Service (QoS) and poor data performance are common problems in WSNs, caused by the data fusion method, where a small amount of bad data can significantly impact the total fusion outcome. In our proposed research, a WSN multi-sensor data fusion technique employing fuzzy logic for event detection. Using the new proposed Algorithm, sensor nodes will collect less repeated data, and redundant data will be used to increase the data's overall reliability. The network's fusion delay problem is investigated, and a minimum fusion delay approach is provided based on the nodes’ fusion waiting time. The proposed algorithm performs well in fusion, according to the results of the experiment. As a result of these discoveries, It is concluded that the algorithm describe here is effective and dependable instrument with a wide range of applications.     

A quantitative method for evaluating the performances of hyperspectral image fusion

Hyperspectral image fusion is a key technique of hyperspectral data processing. In recent years, many fusion methods have been proposed, but there is little work concerning evaluation of the performances of different image fusion methods. In this paper, a method called quantitative correlation analysis (QCA) is proposed, which provides a quantitative measure of the information transferred by an image fusion technique into the output image. Using the proposed method, the performances of different image fusion methods can be compared and analyzed directly based on the images of before and after performing the fusion. The correlation information entropy, based on the developed QCA, is also proposed and testified by numerical simulations. Typical hyperspectral data are applied to the proposed method. The results show that the method is effective, and its conclusions agree with the classification results in applications.     

An information fusion reliability allocation method considering limited sample size circumstances

As an essential part in product reliability design procedure, reliability allocation can connect the reliability index between the overall product and its multiple subsystems. To obtain a reasonable reliability allocation scheme, especially for limited sample size circumstances commonly encountered in aeronautic and astronautic fields, an information fusion allocation method is constructed in the current study. Grey relational analysis (GRA) is incorporated to analyze objective data, while analytic hierarchy process (AHP) is introduced to implement subjective data analysis. Then a final allocation scheme is derived by fusion of the binary information sources. A real application regarding an aeronautic product reliability allocation is given. The sensitivity of allocation result to limited life information circumstances and comparative analysis with reference methods are implemented to demonstrate the reasonability and effectiveness.     

Fundamental performance of novel power supply for HTS magnet using solar energy system

A technical fusion is an important option to establish renewal development in the mutual fields. We have proposed a novel superconducting power supply that is combined with superconducting power supply and solar energy system. An eternal electric energy can be converted by solar energy system, which contains solar panel, photovoltaic (PV) controller and energy-storing battery, can be utilized in the utility power of superconducting power applications. The novel power supply could operate without external utility power to charge the HTS load magnet due to the solar energy. We can improve the operating efficiency and install it in remote locations where utility power is not available. In this paper, as a first step of this work, we showed the possibility of technical fusion between a superconducting power supply and a solar energy system.     

浅海低频声场水声信号时间相关性研究

起伏的声场接收信号是时变的,浅海声场的时间相关性研究有利于目标深度的判别以及水声信号的数据融合。研究浅海低频声场时间相关性以信号的自相关和互相关原理为基础,完成对信号时间相关半径、相关函数值的影响因素分析,得到不同声场条件下信号传播的作用结果。通过仿真比较在不同频率、不同信噪比条件下低频声场信号的相关性曲线,并结合实际海试数据进行验证。研究表明浅海低频声场随机扰动随着低频波长的增加而减弱,且信号时间相关性研究为声场的实际应用提供了一定参考。     

Research work on superconducting magnet systems in Germany

Various applications of sc magnets are pursued in our country. Development in nuclear physics, especially new developments for dc and pulsed superconducting beam line magnets are reported. Research work on magnets for plasma and fusion physics concentrates on systems studies, toroidal systems, and energy storage devices and will become one of the most challenging fields for magnet builders in the future. Industrial applications of sc magnets are investigated for high speed transportation systems, sc machinery and magnetic separation devices. Programs and results are discussed.