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Application of wavelet-based EDA algorithm in detection and location of gas pipeline leak

机译:基于小波的EDA算法在输气管道泄漏检测与定位中的应用

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摘要

Under complex conditions and background noise, gas pipeline leakage is difficult to pinpoint. This paper calculates with EDA based on wavelet analysis of Archimedes copula function, with location accuracy improved significantly. Acoustic emission signal of pipeline leakage not only has short delay, but also carries large amounts of physical information, thus with unique advantage in leak detection and location. According to pipeline detection and location principle of acoustic emission inspection and considering characteristics of city gas pipeline, improvement is proposed for location formula, appropriate wavelet basis and decomposition level plus threshold function are selected to conduct wavelet decomposition and reconstruction of analog experimental leak source signal. With modulus maxima method, more precise time difference of upstream and downstream acoustic signal is obtained. With it as a population sample to apply in EDA algorithm based on Archimedes copula function for optimization of population sample, the result shows that this method can accurately pinpoint gas pipeline leak source.
机译:在复杂的条件和背景噪音下,很难查明天然气管道泄漏。本文基于阿基米德·科普拉函数的小波分析,利用EDA进行了计算,定位精度明显提高。管道泄漏的声发射信号不仅延迟时间短,而且携带大量的物理信息,因此在泄漏检测和定位上具有独特的优势。根据管道检测和声发射检查的定位原理,并结合城市燃气管道的特点,提出了定位公式的改进方法,选择了合适的小波基和分解等级加阈值函数进行小波分解和模拟实验泄漏源信号的重构。利用模极大值法,可以得到更精确的上游和下游声信号时差。将其作为人口样本,应用于基于阿基米德·copula函数的EDA算法,对人口样本进行了优化,结果表明,该方法可以准确地查明天然气管道泄漏源。

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