曲率分块自适应稀疏变换的中子信号通信研究

Study on Neutron Signal Communication Based on Adaptive Sparse Transformation of the Curvature Block

为加快野外测井过程中中子信号的压缩传输通信速度,以及提高获取重构中子信号的信噪比,通过稀疏变换基对中子信号稀疏表示,用硬阈值法滤波稀疏系数求取阈值-稀疏度函数曲线,以曲线最大曲率节点作为自适应阈值,求得最佳稀疏度,并构造自适应有效稀疏基,压缩稀疏系数向量分块传输稀疏信号。实验表明,压缩感知自适应有效稀疏基解决了中子稀疏系数选择难题,加快了中子通信系统传输速度,提高了信噪比。对现场脉冲中子铀定量测井仪系统提供了研究帮助。

The neutron signal communication and transmission processing is the core part of the neutron logging system in the field.Under the condition of pursuing high counting rate,compressed sensing is better than Nyquist sampling theorem for signal reconstruction.In order to speed up the compression,transmission and communication speed of the neutron signal in field logging and improve the SNR of reconstructed neutron signal.The sparse representation of the neutron signal is made by the sparse coefficient with the hard threshold method.The maximum curvature node of the curve is used as the adaptive threshold to obtain the optimal sparsity,and the adaptive effective sparse basis is constructed to compress the sparse coefficient vector and transmit the sparse signal in blocks.The experiments show that the sparse basis based on compressed sensing can effectively solve the problem of neutron sparse coefficient selection,speed up the transmission speed of the neutron communication system and improve the SNR.Conclusions:This study helps for the optimization and improvement of the pulsed neutron uranium quantitative logging tool system in the field.