本文在介绍多小波基本理论的基础上，探讨了基于多小波的信号去噪方法，针对目前多小波去噪的不足，提出一种基于自适应阈值的多小波去噪方法，应用于电力系统输电线故障暂态信号的去噪，并与基于传统阈值多小波和小波的去噪效果进行了比较，仿真结果表明，该方法可以根据实际信号自适应改变阈值大小，在去噪效果上优于传统多小波去噪方法。

在论述基于多分辨分析的小波基构造方法和小波分解理论的基础上，建立了基于离散小波变换的电力暂态信号数据压缩方法。针对电力故障信号基波伴随短时暂态成分的特点，研究了基于信号离散小波逼近品质，即离散逼近时域二范数最大的小波基优化方法。对一实际500kv输电线路故障暂态的分析计算表明，基于优化小波基的离散小波变换对电力故障暂态数据具有较高的压缩比和较小的重构误差。

介绍了连续小波变换定义、基于多分辨分析的Mallat快速小波分解算法。基于EHV输电线路故障暂态电流的特点和暂态保护基本原理，充分利用小波分析的时频局部化特点，建立了基于小波分析的暂态保护启动判据和跳闸判据。借助EMTDC仿真分析软件，研究了一实际电网EHV输电线路故障电弧特点和在不同故障条件下保护判据的有效性，结果表明基于小波分析的暂态保护方案是可行的。

暂态信号分析是电力系统故障诊断和暂态保护的基础和依据，小波变换为暂态信号分析提供了强有力的数学工具。本文讨论了电力系统中常见的暂态信号分析应用，如电力暂态信号检测、去噪与数据压缩以及暂态信号定位等，对这些应用中小波基的选择原则进行了系统的分析研究。仿真分析结果进一步说明了文中提出的选择原则正确性，为小波分析在电力系统中的应用提供了有意义的参考。

The outlines principle from Fourier transform to wavelet analysis technology including Fourier transform, short time Fourier transform, continuous wavelet transform, discrete wavelet transform are presented. Based on this, a E-commerce model applied in electric power market is investigated. in this model, wavelet analysis can be applied to solve series problems. So, wavelet based power system signal de-noises and compression techniques, wavelet based security attestation techniques, wavelet based data mining and information fusion techniques, wavelet based loads forecasting and Electricity price forecasting techniques, wavelet neural networks based data mining and information fusion techniques are discussed.

Many developed countries in the world have adopted high technology to rebuild and improve the rail transportation industry actively. It has increased the security and automation degree of rail transportation greatly. Since "the ninth five-year-plan", the velocity and quality of rail transportation infrastructure construction are improved quickly by applying high technology in China. However, there still have much difference between china and the developed countries in the development of rail transportation. This paper systematically researches the application of high technology in rail transportation such as railway, metro, light railway, railway nearby suburb, maglev railway etc. and also researches the development road to high technology industrialization in transportation field, on the basis of viewing the current development condition and the trend of rail transportation in the world and analyzing the development status and trend of rail transportation in our country.

The front technologies: Linear motor drive technology, unmanned driving technology, and MCS technology, are all advanced technologies of rail transit fields in the world at present. These technologies are applied in some systems such as the subway, the urban light railway, the suburban railway, the high-speed passenger transportation and the heavy freight, which will improve automatic level and bring much more economic utility into rail transit system. So the concepts of those front technologies are introduced, and the work principles are discussed. The purpose is to strengthening people's knowledge of these new technologies and promoting the development of urban rail transit in our country.

This paper discusses the intelligent multi-agent technology, and proposes an intelligent multi-agent based Accurate fault location detection and fault diagnosis system applied in 10kv automatic blocking and continuous power transmission lines along the railway, Agents are software processes capable of searching for information in the networks, interacting with pieces of equipment and performing tasks on behalf of their owner(device). Moreover, they are autonomous and cooperative. Intelligent agents also have the capability to learn as the power supply network topology or environment changed. The system architecture is proposed, the features of each agents are described. Analysis brings forth the merits of this fault location and diagnosis system.

Forecasting the fault and danger in power system and limiting their incidence have been the emphasis in modern power system study. The abundant real-time data gathering in power system contain the complexity and uncertainty of the system, so mining and fusing a series of universal applicable quantities from these data to detect system fault and its stability is essential. Combining wavelet analysis, the modern time-frequency analysis technique, with entropy theory by exploiting their virtue will resolve the problem. In this paper, the feasibility of the wavelet entropy application in power system fault detection and distinguish is analyzed, the wavelet entropy concept based on wavelet analysis is defined, the computation methods of the two kinds of wavelet entropies are established, and the application of the wavelet entropy in transmission line fault detection is simulated and analyzed.