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小波分析在金属磁记忆检测套管故障中的研究

Research on Wavelet Analysis in the Fault Test of Borehole Casing Based on Metal Magnetic Memory

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【作者】 刘子龙张军张新刘洁

【Author】 LIU ZiLong1,ZHANG Jun2,ZHANG Xin3,LIU Jie4(1.Shanghai Jiaotong University,Research Institute of Robotics,Shanghai 200240,China;2.Institute of Shanghai Academy of Spaceflight Technology,Shanghai 201108,China;3.Daqing Petrochemical Company,Daqing 163714,China;4.Core of Measure Control,North East Light Alloy Co.,Ltd.,Harbin 150060,China)

【机构】 上海交通大学机器人研究所上海航天技术研究所大庆石化公司东北轻合金有限责任公司计量控制中心 上海200240上海201108黑龙江大庆163714黑龙江哈尔滨150060

【摘要】 分析了套管承受非均匀载荷而失去平衡,该失衡点为应力集中,易造成套管弯曲、变形或错断.用磁记忆检测方法发现井下套管应力集中区存在较强的磁记忆信号,对其故障早期诊断.对于含有噪声非平稳性的漏磁信号,低分辨率下的小波分解系数全部保留;基于电子测量中的3σ准则确定了高分辨率下的小波系数阈值,进而实现软硬阈值折中消噪.提高了信噪比,准确有效地提取了磁记忆信号中的特征量(梯度).最后,通过实验验证信号处理方法的有效性.

【Abstract】 The stress concentration appears in un-uniform load zone,thereby makes casings bend,deform or break.A typical signal is found in the position of stress concentration for borehole casing using metal magnetic memory testing(MMMT),which can provide early diagnosis of the fault.For nonstationary leakage magnetic signals contain noise,the wavelet coefficients at large scaling remain unchanged,at small scaling the threshold value is determined based on 3σ-rule applied to electronic measurement.Wavelet denoising is a compromising algorithm between the soft-threshold and the hard-threshold of wavelet coefficient.As a result,The SNR is improved and the feature of magnetic signals(gradient) is desirably extracted.Lastly,the validity of the method is demonstrated by experiments.

  • 【文献出处】 测试技术学报 ,Journal of Test and Measurement Technology , 编辑部邮箱 ,2007年04期
  • 【分类号】TG115.284
  • 【被引频次】5
  • 【下载频次】163
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