|本期目录/Table of Contents|

基于最大Lyapunov指数和小波变换的管道检测信号降噪技术

《纳米技术与精密工程》[ISSN:1672-6030/CN:12-1351/O3]

期数:
2009年6期
页码:
0
栏目:
精密测量
出版日期:
2009-11-15

文章信息/Info

Title:
Petroleum Pipeline Detection Signals De-noising Based on the Largest Lyapunov Exponent and Wavelet Transform
作者:
张景川 曾周末 延峰 封皓 靳世久
天津大学精密测试技术及仪器国家重点实验室,天津,300072
Author(s):
ZHANG Jing-chuan ZENG Zhou-mo YAN Feng FENG Hao JIN Shi-jiu
关键词:
分布式光纤传感器 混沌信号 最大Lyapunov指数 小波降噪 油气管道
Keywords:
distributed optical fiber sensor chaotic signal largest Lyapunov exponent wavelet de-noising petroleum pipeline
分类号:
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DOI:
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文献标识码:
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摘要:
针对分布式光纤管道安全预警系统检测信号的混沌特性,最大Lyapunov指数(λ_(max))被定义为降噪指标用于评价各种小波及其阈值组合的降噪性能.基于小波阈值降噪法,采用不同的小波族系和阈值选取及重调方法对现场实测人工挖掘信号进行降噪处理.现场实验数据的分析结果表明检测信号存在混沌特征.在此基础上,λ_(max) 被用于评价小波降噪性能.最后,通过对比实验结果, sym2小波、Sqtwolog阈值选取规则和Mln 阈值重调方法,可以有效地消除现场实测信号中的噪声,达到最优的降噪效果.
Abstract:
Based on the chaotic characteristics of the distributed optical fiber petroleum pipeline safety detection signals, the largest Lyapunov exponent (λ_(max) ) is defined as a performance index to evaluate the de-noising effect of wavelet threshold de-noising methods. Wavelet threshold de-noising methods via combinations of various mother wavelet functions and thresholds have been used to reduce noises from manual digging signals acquired on site. The analysis results have verified the chaotic characteristics of the detection signals and thus λ_(max) was adopted to evaluate the de-noising effect of wavelet threshold de-noising methods. Comparison of the experimental results indicates that the combination of sym2 wavelet, the Sqtwolog threshold selection rule and 'Mln' threshold rescaling method can reduce noises effectively and achieve the best de-noising performance.

参考文献/References

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备注/Memo

备注/Memo:
国家自然科学基金重点项目,教育部高等学校博士学科点专项科研基金
更新日期/Last Update: 2009-12-20