Detection of Abrupt Change Based on Innovation Theory and Leak Detection in Pipeline
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摘要: 在ESPRT检测方法的基础上,结合新息过程给出了一种新的变点检测方法.利用ESPRT方法检测经新息模型产生的新息过程,实现了模型参数变点的非参数检测,扩展了ESPRT方法在实际应用中的适用范围.将该方法应用于长输管道泄漏故障监测时,利用基于BP神经网络的非线性时间序列预测方法建立了管道泄漏监测系统的新息模型以及泄漏检测模型.将上述监测方法应用于实验泄漏水管道,能在线实时有效地发现泄漏.Abstract: The paper presents a new detection method of abrupt change based on extended sequential probability ratio test (ESPRT) innovation process. This method can convert a parameter model into a non-parameter model using innovation theory. So, the method can be widely applied to practice in combination with ESPRT. The paper uses nonlinear temporal series based on BP neural network to establish the innovation model and leakage detection model of the pipe. It is proved that the detection method can effectively online detect the leak, using the collected data in the laboratory.
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Key words:
- Sequential test /
- innovation /
- leakage detection /
- pipeline
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