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计算机工程 ›› 2012, Vol. 38 ›› Issue (7): 13-15. doi: 10.3969/j.issn.1000-3428.2012.07.005

• 博士论文 • 上一篇    下一篇

基于复Morlet小波的地层钻探识别

能昌信1,金朝娣1,2,刘玉强1,刘景财1,董 路1   

  1. (1. 中国环境科学研究院固体废物污染控制技术研究所,北京 100012;2. 中国矿业大学(北京)机电与信息工程学院,北京 100083)
  • 收稿日期:2011-04-03 出版日期:2012-04-05 发布日期:2012-04-05
  • 作者简介:能昌信(1964-),男,副教授、博士后,主研方向:计算机控制,环境监测;金朝娣,博士研究生;刘玉强、刘景财,工程师;董 路,研究员
  • 基金资助:
    国家“863”计划基金资助重点项目(2007AA061303); 中央级公益性科研基金资助项目“重金属(铬)污染场地污染特性快速识别技术研究”(2009KYYW04)

Stratum Identification of Drilling Based on Complex Morlet Wavelet

NAI Chang-xin   1, JIN Zhao-di   1,2, LIU Yu-qiang   1, LIU Jing-cai   1, DONG Lu   1   

  1. (1. Institute of Solid Waste Management, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; 2. School of Mechanical Electronic & Information Engineering, China University of Mining and Technology, Beijing 100083, China)
  • Received:2011-04-03 Online:2012-04-05 Published:2012-04-05

摘要: 在低信噪比时,短时傅里叶变换和实小波变换无法准确提取钻头进入不同地层的时延信息。为此,提出一种复小波变换分析法。利用幅值和相位信息对信号突变点进行提取和定位,从而实时判断钻头钻进目的层的时刻。实验结果表明,该方法能准确表征振动信号的时频特征,与短时傅里叶变换和实小波变换相比,具有更好的时间定位和抑噪能力。

关键词: 复Morlet小波, 短时傅里叶变换, 实小波变换, 振动信号, 地层识别, 相位

Abstract: According to the bit excited in the layers with different characteristics of the vibration signal, the delay information of the bit into an another stratum can not be extracted accurately by real Short Time Fourier Transform(STFT) and wavelet transform in the case of low SNR. This paper puts forward a complex Morlet wavelet transform analysis. The message of the amplitude and the phase has a good sensitivity to the mutation, so the mutation position can be extracted and then the time when the drilling bit is into different stratum is determined in real time. Experimental result prove that complex Morlet wavelet transform can accurately characterize the time-frequency information and the delay time information. Compared with the STFT and the real wavelet transform, complex Morlet wavelet transform has a better time localization and noise suppression capabilities.

Key words: complex Morlet wavelet, Short Time Fourier Transform(STFT), real wavelet transform, vibration signal, stratum identification, phase

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