摘要
分布式监测系统长时间的连续监测会产生大量的状态参数,为了数据实时连续传输及节省以数据流量计费的数据传输成本,在分析分布式监测系统传输模型基础上,对无损压缩方法中的霍夫曼编码和LZW算法进行了研究;针对缓变信号相似程度高的特点,提出了基于动态规划的霍夫曼编码和LZW数据压缩算法,使用上述方法,对发动机状态监测数据进行压缩,通过比较,基于动态规划的霍夫曼编码方法压缩率最高,对于水温、油温、油压性能参数的压缩率均在60%以上,该方法成功应用于大型复杂装备分布式监测系统中,有效减少了信号冗余度,提高了数据传输效率。
A mass of monitoring condition data is produced in distributed monitoring system for a long time. In order to transmit continu- ously and economize for data input stream, lossless compression methods of Huffman coding and LZW algorithm are researched on basis of analyzing the transmitting model. In view of the characteristics of a high similar degree for slowly varying signals, data compression methods of Huffman coding and LZW based on dynamic programming are put forward. The engine condition monitoring data is compressed through the methods above. By comparison, the Huffman coding based on dynamic programming has the highest compression ratio, which is over six- ty percent for the performance parameters of water temperature, oil temperature and oil pressure. The method is successfully applied in dis- tributed monitoring system for large-- scale mobile complex equipment to reduce the data redundancy and improve the efficiency of data trans- mission.
出处
《计算机测量与控制》
北大核心
2014年第3期926-929,共4页
Computer Measurement &Control
基金
国家自然科学基金项目(51205405)
军队重点科研项目([20XX]X号)
关键词
分布式监测
霍夫曼编码
LZW算法
动态规划
distributed monitoring
Huffman coding
LZW algorithm
dynamic programming
