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基于小波包-Haar小波变换的漏磁检测信号降噪数据压缩方法
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重庆博士后基金资助项目(XM2014099)


MFL Signal Denoise and Data Compression Method Based on Wavelet Packet-Haar Wavelet Transform Algorithm
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    摘要:

    漏磁检测是对输油管道、油罐等设备缺陷进行无损检测的一种重要方法,但在检测过程中产生的信号数据量庞大,同时会产生多种干扰噪声,出现信号失真、漂移和信号被湮没等问题,对信号进行降噪滤波是缺陷漏磁检测的关键环节。探讨了信号降噪压缩方法,研究了基于小波包-Haar小波算法的漏磁检测信号降噪压缩算法,通过该算法,在对信号数据进行降噪压缩处理同时,保留了高频部分信号特征,从而在降噪后数据解压缩过程中避免了信号失真畸变的现象。

    Abstract:

    For pipelines, tanks and other equipment defects, magnetic flux leakage inspection is an important nondestructive testing method, but the huge amount of signal data will be generated in the testing process, and it will produce a variety of interference and noise, occurring problems such as signal distortion, drift, and annihilation etc. Signal noise reduction filter is key for magnetic flux leakage defect detection. The signal noise reduction compression method was explored. The compressed MFL signal denoising wavelet packet-Haar wavelet algorithm was studied. By this algorithm, signal data were compressed to reduce noise while the high frequency signal characteristics were retained, resulting in avoiding the phenomenon of signal distortion aberration in data decompressing process.

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宋志强,张莹,吴江.基于小波包-Haar小波变换的漏磁检测信号降噪数据压缩方法[J].机床与液压,2017,45(2):126-129.
. MFL Signal Denoise and Data Compression Method Based on Wavelet Packet-Haar Wavelet Transform Algorithm[J]. Machine Tool & Hydraulics,2017,45(2):126-129

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  • 收稿日期:2015-12-14
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  • 在线发布日期: 2017-05-09
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