Pipeline leakage signal time delay estimation method based on mean decomposition and signal definition

Abstract

The invention relates to a pipeline leakage signal time delay estimation method based on mean decomposition and signal definition, and belongs to the technical field of fluid pipelines. The method comprises the following steps that S1, two paths of pipeline leakage signals X1 (t) and X2 (t) are collected; S2, the two paths of pipeline leakage signals are subjected to LMD decomposition correspondingly to obtain a plurality of PF components with physical significance; S3, PF components are screened through a signal definition algorithm, and pipeline leakage signals X'1 (t) and X'2 (t) are reconstructed; and S4, the reconstructed signals X'1 (t) and X'2 (t) are subjected to cross-correlation operation to obtain time delay estimation. The leakage signals are decomposed through the LMD algorithm to obtain the plurality of PF components with physical significance. A main PF component is selected through the signal definition algorithm, and the leakage vibration signals are reconstructed; andthe new leakage vibration signals formed by reconstruction are subjected to cross-correlation time delay estimation to obtain time delay estimation.

Description

technical field [0001] The invention belongs to the technical field of fluid pipelines, and relates to a pipeline leakage signal time delay estimation method based on mean value decomposition and signal clarity. Background technique [0002] Pipelines are widely used in the transportation of natural gas, oil and other fluids, and are an efficient and convenient method of fluid transportation. Pipeline aging, natural disasters and other reasons often lead to pipeline leakage, causing huge losses to people's lives and property. Therefore, in order to effectively avoid the harm caused by pipeline leakage, the detection and location technology of fluid pipeline leakage is very important. Chinese patent (CN108332063A) discloses a pipeline leakage location method based on a cross-correlation algorithm. The two time-domain pipeline leakage signals collected by the sensor are directly Fourier transformed, and the cross-spectral density function is weighted in the frequency domain. ...

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Problems solved by technology

The pipeline leakage signal is decomposed into multiple components by the LMD algorithm, and the component with the source signal cross-correlation method is used to screen out the components with obvious peaks to reconstruct the pipeline leakage signal, thereby suppressing the noise of the pipeline leakage signal, but if the pipeline leakage signal The signal-to-noise ratio is too low, and the cross-correlation method may filter out the main leakage component and select the component containing the noise signal for reconstruction, resulting in a large delay estimation error

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