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Leaks Detection in a Pipeline Using Artificial Neural Networks

机译:使用人工神经网络的管道泄漏检测

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摘要

A system based on Artificial Neural Networks (ANN) is proposed to detect and diagnose multiple leaks in a pipeline leaks by recognizing the pattern of the flow using only two measurements. A nonlinear mathematical model of the pipeline is exploited for training, testing and validating the ANN-based system. This system was trained with tapped delays in order to include the system dynamics. Early results demonstrate the effectiveness of the approach in the detection and diagnosis of simultaneous multiple faults.
机译:提出了一种基于人工神经网络(ANN)的系统,通过仅使用两次测量即可识别流型,从而检测和诊断管道泄漏中的多个泄漏。利用管道的非线性数学模型来训练,测试和验证基于ANN的系统。该系统经过分接延迟培训,以包括系统动态。早期结果证明了该方法在同时发生多个故障的检测和诊断中的有效性。

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