城市地下管网运维大数据预处理技术研究

Research on monitoring data acquisition and preprocessing technology of underground pipe network based on subsection interpolation

在城市建设中有错综复杂的地下管网,迫切需要建立地下管网数据智能化建设的智能检测系统,对地下管网数据存在各种风险进行监测.多段复杂的地下管网数据错综复杂,结构不一且数据量多,Tian差值扩展技术不再适用.非线性DELTA误差数据压缩算法和分段差值法解压缩算法是数据处理过程的两种不同数据预处理技术,利用分段差值法对解压缩的数据进行填补,得到的数据能更加准确的复合地下管网平台的要求.根据市政工程建设运维数据特点,提出分段差值法处理市政监控数据解压缩算法过程.采用分段差值扩展和非线性Delta误差技术方法嵌入数据,减少不可扩展差值的数量,提高管网数据的压缩率,根据差值次低位的可改变性定位不可变差值,从而提高数据嵌入容量,提取端在提取信息后可根据需要无损地恢复原始数据.实验结果表明,该算法在保证数据质量的同时,数据容量有较大的提高,并有效抑制数据冗余,基于分段差值法的地下管网数据解压缩算法得到的数据利用率增加了83.3%.

There are complex underground pipe networks in urban construction,so it is urgent to establish an intelligent detection system for the intelligent construction of underground pipe network data to monitor various risks of underground pipe network data.The data of multi-segment complex underground pipe network is complex,the structure is different and the amount of data is large.The nonlinear delta error data compression algorithm and the segment difference method decompression algorithm are two different data preprocessing technologies in the data processing process.The segment difference method is used to fill the decompressed data,and the data obtained can meet the requirements of the composite underground pipeline network platform accurately.According to the characteristics of operation and maintenance data of municipal engineering construction,this paper puts forward the algorithm process of decompressing municipal monitoring data by the method of subsection difference.In order to reduce the number of non-expandable differences and improve the compression rate of pipe network data,segment difference expansion and non-linear delta error technology are used to embed data,and the immutable difference is located according to the variability of the lower order of the difference,so as to improve the data embedding capacity.After extracting information,the extraction end can restore the original data without damage according to the needs.The experimental results showed that the algorithm not only ensured the data quality,but also greatly improved the data capacity and effectively suppresses the data redundancy.The data utilization rate of the data decompression algorithm based on the subsection difference method was increased by 83.3%。