【作者】 胥峰；

【导师】 林建泉；

【作者基本信息】 西南交通大学 ， 电力系统及其自动化， 2012， 硕士

【摘要】 历史数据库是SCADA系统的一个重要组成部分,数据库中长期积累的数据是SCADA系统的宝贵资源,为管理人员分析和处理故障提供了第一手资料,同趋势分析、事件处理、报表打印等服务紧密结合。随着铁路跨越式的的改革与发展和铁路的第六次提速的顺利进行,电铁SCADA系统朝着大系统和网络化控制系统方向发展。这种新型的PSCADA分布式系统,调度中心所需采集的信息量越来越大,要确保这些海量的数据能够实时存储,并尽可能地节约存储成本,提高存储效率,必须对数据进行有效的压缩处理。本文在充分考虑电铁SCADA系统实时历史数据库和历史数据的特点的前提下,对历史数据的压缩策略与压缩算法进行了研究,研究结果概述如下：1)研究了SCADA系统中实时历史数据库系统。首先分析了实时历史数据库的系统特点,其次详细地说明了数据库中数据分布和数据读写流程,最后根据历史数据库中数据的特点,阐明了数据压缩的可行性和必要性。2)研究了无损压缩技术。首先介绍了数据压缩的概念,阐述了数据压缩的原理、分类和应用。其次对无损压缩算法中包括基于统计模型的压缩算法,LZ系列基于字典模型的压缩算法和其它算法等算法的原理及实现通过实例进行全面讲解,最后使用C++实现了PPM编码、LZW编码、BWT编码的编程,对这三种编码算法进行性能比较。3)研究了有损压缩技术。对在实时历史数据压缩中应用最为普遍的旋转门算法进行了研究,通过仿真测试说明在旋转门算法中是影响压缩质量与性能的唯一设定值。一旦压缩偏移量参数设置与实际数据特性不符,将严重限制了SDT算法的性能。因此研究了一种改进的旋转门算法,可以自适应的调整压缩偏移量,并对改进的旋转门算法进行仿真测试。4)研究了数据压缩技术在实时历史数据库中的实现,通过动态链接库实现数据压缩和解压模块,研究数据压缩模块的总体框架,针对时间戳、开关量、整型量和模拟量分别采用了不同的数据压缩方法。更多还原

【Abstract】 As an important component of SCADA system, historical database saves important data in SCADA system day and night, so it provides first-hand information for management analysis of processing failures. In addition, historical database plays a great part in trend analysis, event processing, report printing and other services. With the reform and development of the railway and smooth progress of The sixth speed, the PSCADA system develop to the direction of large systems and networked control systems. The information which collected by the dispatch center in the new PSCADA distributed system is growing. The data must be effectively compression to ensure the vast amounts of data to real-time storage, to save storage costs as much as possible and improve storage efficiency. This paper researches the historical data compression strategy and the compression algorithm with the premise of fully considering of the characteristics of real-time history of the PSCADA system database and historical data. The findings are summarized as follows:1) The real-time history database system in SCADA system. Firstly, the characteristics of the real-time historical database are analyzed. Secondly, we describe the data distribution in the database and data reading and writing process. Finally, according to the characteristics of data in the historical database, we clarify the feasibility and necessity of data compression.2) Lossless compression technique is researched. Firstly, we introduce the concept principle, classification and application of data compression. Secondly, we explain fully the principle and implementation of the lossless compression algorithms include compression algorithm based on the statistical model, LZ series based on the dictionary model and other algorithms through examples. Finally,we implement three coding algorithms including the PPM encoding, the LZW encoding, the BWT encoding by C++.3) Lossy compression techniques are researched. The SDT algorithm which is most common in the real-time historical data compression is researched. We can see that the compression parameters E affect the compression quality and performance in the SDT algorithm through the simulation. Once E is does not match with the actual data characteristics, There will be severely limitation in the performance of the SDT algorithm. So we study an improved SDT algorithm which can adaptively adjust the E, and do the simulations.4) The application of the data compression technology in real-time history database is researched in this paper. The data compression and decompression module are achieved through the dynamic link library. The overall framework of the data compression module is reaearched. Different signals.such as:timestamp, switch type, integer type and analog type,have different recording methods.更多还原