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Chaotic characters based oil pipeline leak detection method and system

机译:基于混沌的字符油管道泄漏检测方法和系统

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摘要

Pipeline transportation is the main way of crude oil and product oil transportation, pipeline leak detection and positioning in time is very important to safe operation of the pipeline. The currently existing leak detection methods based on negative pressure wave are consider the interference existing in steady oil transportation state as random disturbance, which cause the difficult to detect tiny leak. But the existing studies have proved that when the oil transportation is steady, the pipeline the pressure shows the chaotic characteristics. In this paper, according to the chaotic characteristic in oil pipeline transportation, we design a oil pipeline leak detection methods, in which the algorithm adopts the combination of median and wavelet filter method, anomaly detection based on RBF neural network and fuzzy min-max classification method. At last we give the structure of pipeline leak detection system, in which the proposed leak detection method is the key method.
机译:管道运输是原油和产品油运输的主要方式,管道泄漏检测和定位及时对管道安全运行非常重要。基于负压波的目前现有的泄漏检测方法考虑在稳定的油运输状态中存在的干扰作为随机干扰,这导致难以检测到微小泄漏。但现有的研究证明,当油运输稳定时,管道压力显示混沌特性。本文根据石油管道运输的混沌特性,我们设计了一种石油管道泄漏检测方法,其中算法采用中位数和小波滤波法的组合,基于RBF神经网络的异常检测和模糊MIN-MAX分类方法。最后,我们给出了管道泄漏检测系统的结构,其中提出的泄漏检测方法是关键方法。

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