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Lossless Compression of Pipeline Magnetic Flux Leakage Inspection Data Based on Integer Lifting Wavelet Transform

机译:基于整数提升小波变换的管道磁通泄漏检测数据无损压缩

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Pipeline Magnetic Flux Leakage (MFL) inspection device with high resolution generates a great deal of data. An effective technique of online data compression is urgently needed. Loss data compression will ignore both noise and useful weak MFL signal, so lossless data compression is necessary. First-order differencing is used to eliminate signal variance generated by the variance of sensors lift-off. Differenced MFL image is integer lifting wavelet transformed with integer CDF(2,2) biorthogonal wavelet. SPIHT (Set Partitioning in Hierarchical Tree) algorithm is used to code the transformed data, and then lossless data compression is implemented. The compression ratio of inspection data for the pipeline with defect is above 3:1, and for the pipeline without defect the compression ratio is above 6:1. The algorithm has a good real-time characteristic and is easy to hardware implementation.
机译:管道磁通泄漏(MFL)具有高分辨率的检查装置产生大量数据。迫切需要一种有效的在线数据压缩技术。损耗数据压缩将忽略噪声和有用的弱MFL信号,因此需要无损数据压缩。一阶差异用于消除通过传感器剥离的方差产生的信号方差。差异的MFL图像是用整数CDF(2,2)Biorthogonal小波变换的整数提升小波。 SPIHT(在分层树中设置分区)算法用于编码转换的数据,然后实现了无损数据压缩。管道对缺陷的检查数据的压缩比在3:1之上,并且对于没有缺陷的管道,压缩比高于6:1。该算法具有良好的实时特性,易于硬件实现。

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