摘要
地铁机车牵引传动系统仿真模型复杂、仿真时间长、仿真精度高,与其相关的数据量非常大。若要实现对地铁机车的牵引传动系统的仿真分析,同时存储仿真分析结果,就必须删除系统仿真产生的冗余数据。结合南京地铁西延线地铁机车牵引传动系统仿真软件——TSim产生海量数据的问题,该文提出了一种有针对性的自适应在线压缩算法。该压缩算法根据牵引传动系统仿真产生的数据结构的不同,对仿真数据做了特殊处理并设计了相应的子压缩算法。实验结果表明:该压缩算法能够在保证失真度最小的前提下,在最大程度上减少了仿真数据量,节省了存储的时间与空间,加快了后续处理速度,提高了牵引传动系统仿真的效率。
Due to the complex of the Metro Vehicles electrical model, the long time Simulation and the high precision Simulation, mass data is produced during the simulation. To achieve the simulation and analysis for Metro Vehicles and store the results, it' s necessary to delete redundant data to reduce the amount of data. Combination the problem of huge amounts of data produced by the simulation software of the Traction Drive System on Nanjing Metro Vehicles West Extension Line Tsim, the paper presents a targeted online adaptive compression algorithm. Based on the different structures of the Traction Drive system simulation data, special deals are taken and the corresponding sub-compression algorithm designed. The experimental results show that: under the premise of the minimum distortion , the compression algorithm could reduce the amount of simulation data in the maximum extent possible, time and storage space saved, the rate of follow-up treatment accelerated, the efficiency of the simulation system improved.
出处
《数字技术与应用》
2009年第10期30-31,共2页
Digital Technology & Application
关键词
地铁机车
牵引传动系统仿真
海量数据
自适应在线压缩
失真度
压缩比
Metro Vehicles
electrical system stimulated
mass data
adaptive online compression
compression ratio
distortion