基于改进科学计算浮点数压缩算法的工业远程监控数据无损压缩方法

为解决大量工业远程监控数据在通用分组无线服务(GPRS)网络上的传输延迟问题,提出了基于改进科学计算浮点数压缩(FPC)算法的工业远程监控数据无损压缩方法.首先,根据工业监控数据中浮点数部分的特点对原FPC算法中的预测器结构进行改进,并将该改进算法作为浮点数部分的压缩算法; 然后,与区间编码相结合作为整个数据域的压缩方法.改进前后的浮点数部分压缩实验结果表明改进的FPC算法提高了预测器的预测精度,且在保持较高压缩效率的同时提高了压缩率.与通用无损压缩算法相比,所提算法提高了12%以上的平均压缩率,减少了38.5%以上的平均压缩时间,使得传输时间降低了23.7%以上,在传输数据量大且传输速率不高的情况下大大提高了监控的实时性.

Lossless compression method of industrial remote monitoring data based on improved floating point data compression

In order to solve the problem that a lot of industrial remote monitoring data transmission would leads to the transmission delay on General Packet Radio Service (GPRS) network, a lossless compression method of industrial remote monitoring data based on improved FPC (Floating Point data Compression) was proposed in this paper. First of all, according to the characteristics of industrial remote monitoring data, the structure of predictor in original FPC algorithm was improved, and then was combined with range encoding algorithm to compress the entire monitoring data. The experimental results show that the prediction precision of improved FPC is higher than before, and the compression ratio is enhanced with the same high compression efficiency. The results of comparison experiments between the proposed method and general lossless compression algorithms show that, the average compression ratio is increased more than 12% and the average compression time is decreased more than 38.5%, which leads to the result that the transmission time is decreased more than 23.7%. The method can increase real-time monitoring performance when network transmission rate is very low and transmission data is very large.