面向供应链系统的RFID信息服务关键技术研究

众所周知，供应链管理(Supply Chain Management, SCM)是一个极其复杂的系统，自从上个世纪70年代以来，经济全球化的趋势以及信息技术的快速发展，给本来已经极其热门的供应链管理领域又提供了无穷的发展空间。这个领域里面不断出现新的挑战，其中的种种难题几乎都跟供应链系统的复杂性和不确定性特征息息相关。 无线射频识别（Radio Frequency Identification，RFID）技术是通过无线射频方式进行非接触双向通信的自动化识别与数据获取技术，在多目标识别、移动目标识别和单品识别等应用领域具有极大的优势，广泛应用于国防、制造、医疗、零售、物流等诸多领域，被誉为21世纪最热门的技术之一。近年来RFID技术受到工业界和学术界高度关注，理论研究和实践应用得到了突飞猛进的发展。随着无线射频识别技术的迅速发展和价格的迅速低廉，企业已经越来越多地把信息技术应用于供应链的管理之中，信息技术已成为企业实施供应链管理的不可或缺的手段，它们可以使企业的供应链管理更为有效以及高效。但是在将RFID技术应用到供应链信息管理的过程之中，遇到了许多阻力和困难。在RFID信息网络的构建、网络中海量资源调用、以及跟踪应用等诸多方面都存在还不能解决的问题。 本文在深入研究无线射频识别技术的基础上，结合供应链信息系统的发展现状以及所面临的诸多迫切需要解决的问题，提出了面向供应链服务的RFID信息网络，并设计了RFID网格模型，对RFID网络中的资源优化问题，以及目标跟踪问题进行了专门的研究，提出了行之有效的算法。主要的研究内容包括以下几个方面： 首先，构建了基于RFID系统的供应链信息管理系统的架构，并针对供应链信息系统中存在的种种问题，提出构建面向供应链服务的RFID网络。在详细介绍了当前国内外RFID网络研究与发展的基础上，设计了基于RFID网络的供应链应用体系，并给出了这一RFID网络的基本架构。 其次，根据网格计算理论提出了RFID无线网格体系，分别对RFID无线网格分层组织和系统构建组成进行了详细的描述。设计了RFID网格的供应链应用场景，将RFID网格基础设施安装在制造商分销中心、零售商仓库和零售商商店，通过运行在每个基础实施构件提供RFID数据捕获、数据处理和集成，并对RFID无线网格体系进行了建模以及分析。 再次，针对供应链系统的RFID信息服务瞬时产生海量的RFID信息，资源调度优化存在难点，提出利用粒子群算法，解决这一问题。该算法在求解该类问题时的优点包括：收敛速度快、容易克服早熟、能够优化多目标、能够柔性控制和容易分布式运算等。我们设计了RFID资源任务调度模型，利用经过改进的粒子群算法BPSO对这一模型的进行了求解，并将这一算法与传统的遗传算法的求解进行了仿真比较，可见该算法较遗传算法有较大优势。 最后，在面向供应链系统的RFID信息服务中，跟踪领域具有广泛的应用前景，同时在对环境敏感的对象跟踪领域中联合无线传感器网络也是RFID跟踪应用的一大趋势。针对网络跟踪研究，总结了RFID与无线传感器网络相结合的三种模式，提出以Adhoc的方式将RFID读写器组成一个面向供应链服务的无线跟踪网络，并给出一基于RFID无线网络的跟踪算法，以解决供应链系统中物品的追踪问题。

UHF RFID 射频前端及其编解码设计

射频识别（Radio Frequency Identification，RFID）技术，是一种利用射频通信实现的非接触式的数据采集和自动识别技术（以下通称RFID技术）。而超高频射频识别技术（Ultra High Frequency RFID，UHF RFID）具有识别距离远、识别准确率高、识别速度快、抗干扰能力强等特点而成为当前研发的热点。UHF RFID读写器的难点就在于射频前端电路和基带编解码的设计，它们设计的好坏直接决定了读写器的性能好坏。 本文首先通过介绍UHF RFID读写器射频前端设计的基本原理，采用射频通用收发模块进行射频前端设计的方法，给出了以ADF7020收发芯片为核心的UHF RFID读写器的射频前端的整体设计和具体的实现电路，设计了包括射频收发电路、射频前端匹配电路、滤波电路、环行器电路、功率放大电路等。 其次根据EPC Gen-2的协议标准进行了UHF RFID读写器的基带编码解码的仿真设计，然后开发了以FPGA为核心的完整的数字基带硬件电路，实际调试表明整个基带编解码软件在硬件基带PCB板上运行状况良好，并能对EPC Gen-2的协议标准的命令进行正确的编码解码。 最后通过研究学习软件无线电的理论和开发方法，把UHF　RFID读写器的射频前端分成射频模拟前端和射频数字前端，给出了一种基于软件无线电思想的UHF RFID射频数字前端设计模型，并借助于SIMULINK中的信号处理工具箱对构建的数字前端的进行仿真验证，仿真结果验证了用软件无线电实现UHF RFID数字前端的可行性。

KEL-TI介质的地震波场响应与成像方法研究

To deal with the problems in multi-component converted seismic wave exploration in coal fields, the wave propagating features and imaging methods of multi-component converted waves in coal measure strata are researched in this thesis firstly. The relations between viscoelasticity and anisotropy in coal measure strata are analyzed to build KEL-TI model, and which seismic wave propagating and attenuating features are researched. The disadvantages of converted wave imaging methods based on common converted point gather are analyzed and constant velocity no NMO converted wave imaging method based on common scattering point gather is put forward, according to Huygens-Fresnel principle, which applicabilities in the elastic isotropic, elastic TI and KEL-TI situations are discussed. To different model simulation data, the common scattering point gathers’ and stacked profiles’ features are analyzed. The results show that the method can image compressional waves and converted waves with high precision. Secondly, the resolution enhancing theories and methods of converted wave are researched by Rayleigh wave suppressing, converted wave static correction and poststack inverse-Q filtering. 1) The polarization filter is designed by the instantaneous polarization information of seismic waves, and the Rayleigh wave suppressing method is researched. From the spectrum analysis before and after filtering, it can be derived that the amplitudes are kept relatively. 2) To constant velocity no NMO converted wave imaging method, the static correction method based on common equivalent offset point gather is put forward and tested to the actual converted waves. 3) The relation between equivalent quality factor of converted wave, compressional wave quality factor and the ratio of compressional to shear wave velocity is derived. The compressional wave quality inversion method by first arrivals of none-offset VSP is researched, and which is then transformed to the equivalent quality factor to perform inverse-Q filtering of actual converted waves. The result has shown that the method can recover the high frequency energy of converted waves. At last, the theories and methods researched in this thesis are practiced to the 3D3C seismic exploration in Guqiao coal mine in Huainan and achieve good results.

HHT在电磁信号处理中的应用

In modem signal Processing，non－linear，non－Gaussian and non－stable signals are usually the analyzed and Processed objects，especially non－stable signals. The convention always to analyze and Process non－stable signals are： short time Fourier transform，Wigner－Ville distribution，wavelet Transform and so on. But the above three algorithms are all based on Fourier Transform，so they all have the shortcoming of Fourier Analysis and cannot get rid of the localization of it. Hilbert－Huang Transform is a new non－stable signal processing technology，proposed by N. E. Huang in 1998. It is composed of Empirical Mode Decomposition (referred to as EMD) and Hilbert Spectral Analysis (referred to as HSA). After EMD Processing，any non－stable signal will be decomposed to a series of data sequences with different scales. Each sequence is called an Intrinsic Mode Function (referred to as IMF). And then the energy distribution plots of the original non－stable signal can be found by summing all the Hilbert spectrums of each IMF. In essence，this algorithm makes the non－stable signals become stable and decomposes the fluctuations and tendencies of different scales by degrees and at last describes the frequency components with instantaneous frequency and energy instead of the total frequency and energy in Fourier Spectral Analysis. In this case，the shortcoming of using many fake harmonic waves to describe non－linear and non－stable signals in Fourier Transform can be avoided. This Paper researches in the following parts： Firstly，This paper introduce the history and development of HHT，subsequently the characters and main issues of HHT. This paper briefly introduced the basic realization principles and algorithms of Hilbert－Huang transformation and confirms its validity by simulations. Secondly, This paper discuss on some shortcoming of HHT. By using FFT interpolation, we solve the problem of IMF instability and instantaneous frequency undulate which are caused by the insufficiency of sampling rate. As to the bound effect caused by the limitation of envelop algorithm of HHT, we use the wave characteristic matching method, and have good result. Thirdly, This paper do some deeply research on the application of HHT in electromagnetism signals processing. Based on the analysis of actual data examples, we discussed its application in electromagnetism signals processing and noise suppression. Using empirical mode decomposition method and multi-scale filter characteristics can effectively analyze the noise distribution of electromagnetism signal and suppress interference processing and information interpretability. It has been founded that selecting electromagnetism signal sessions using Hilbert time-frequency energy spectrum is helpful to improve signal quality and enhance the quality of data.