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一种小波变换信号处理方法 被引量:9

Algorithms and application of the wavelet-based signal processing
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摘要 针对钻井泥浆脉冲信号在复杂环境中传输的问题,建立了复合泥浆信号模型,研究了符合信号特征、基于最低熵的最优小波设计及处理方法.利用该小波对信号进行变换,分析信号、噪声和基线的模极大值传播特性,提出了模极大值平方后与相邻系数相乘且归一化的处理方法,实现噪声去除、基线矫正和脉冲位置检测.该方法在中国石油某油田得到现场应用,处理采集的钻井泥浆信号,检测脉冲位置恢复原始编码数据,可满足随钻测井的要求. Confined to the measuring and transmitting conditions in the field, the mud signal model is usually set which contains all kinds of noises. In order to manipulate the signals, an optimal wavelet is designed according to the characteristics of the signals based on the minimum entropy. By using the wavelet, the modular maximum of signals, noises and the baseline are calculated for different scales. The advanced processing algorithms for the modular maximum are conducive to noise-reduction, baseline correction, and singularity detection. The algorithms have been applied with satisfactory results in the Measure While Drilling system in some oil field.
出处 《西安电子科技大学学报》 EI CAS CSCD 北大核心 2009年第4期751-755,共5页 Journal of Xidian University
基金 油气资源与勘探技术教育部重点实验室(长江大学)资助(2006K002)
关键词 泥浆信号 小波变换 模极大值 去噪 基线矫正 突变检测 mud signal wavelet transforms modular maximum noise reduction baseline correction singularity detecting
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参考文献15

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二级参考文献60

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