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Chaotic characters based oil pipeline leak detection method and system

机译:基于混沌特征的输油管道泄漏检测方法及系统

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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:管道运输是原油和成品油运输的主要方式,管道泄漏的及时检测和定位对管道的安全运行非常重要。现有的基于负压波的泄漏检测方法将稳态输油状态下的干扰视为随机干扰,导致难以发现微小泄漏。但是现有研究证明,在输油稳定的情况下,管道压力呈现出混沌特性。本文针对输油管道运输的混沌特性,设计了一种输油管道泄漏检测方法,该算法采用中值和小波滤波相结合的方法,基于RBF神经网络的异常检测和模糊最小-最大分类方法。最后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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