基于多节点样条理论的漏磁数据去冗余压缩算法

为解决管道漏磁缺陷检测中采样数据的去冗余压缩问题，在利用小波去噪的基础上，根据多节点样条理论具有插值过程无需解方程组、逼近误差小、基函数有界支集的性质，通过构造一个对称的、局部支集的、拉格朗日型基函数，从而设计出一种能快速、高效地逼近原检测数据的去冗余压缩新算法，以提高管道漏磁在线检测数据压缩的实时性．用实验室检测到的漏磁数据对该算法进行了验证．结果表明，该算法具有很好的实时性及较高的数据压缩率．

Removing Redundancy Data Compression Algorithm of MFL Inspecting Based on Many-Knot Spline Theory

In order to remove redundancy data and compress sampling data in the process of magnetic flux leakage(MFL) inspecting, this paper used wavelet theory to get rid of the signal noise included in the MFL inspecting of pipelines firstly, constructed a symmetry and local branch set's function based on many-knot spline theory, which need not settle the equation group, has small approaching error and finite-bound branch set, and designed a speed and high efficiency data compression algorithm to approach the original MFL inspecting data. Through the verification of algorithm on the data obtained from laboratory, the result indicates that it has high compression ratio and good real-time feature for offshore pipeline MFL on-line inspection.