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Pipeline defect identification method of suppression-end intrinsic time scale decomposition

A technology of inherent time scale and defect identification, applied in the field of information detection, which can solve problems such as end-effects easily

Active Publication Date: 2018-06-12
BEIJING UNIV OF TECH
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Problems solved by technology

[0004] The technical problem to be solved by the present invention is to use symmetric continuation to process the extremum sequence for the problem that the intrinsic time scale decomposition is easy to produce the endpoint effect, and the processed extremum sequence adopts the intrinsic time scale decomposition to obtain the intrinsic rotation component

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Embodiment Construction

[0070] The pipeline defect identification method based on the inherent time scale decomposition of the suppression end of the present invention, such as figure 1 As shown, its main steps include:

[0071] Step 1: Use the fluxgate probe to collect the magnetic signal x(t) of the pipeline. According to the actual signal x((t), select the number of decomposition layers of the inherent time scale decomposition of the suppression end, and iterate to terminate the error.

[0072] Step 2: Extract the number of extreme points, coordinates of extreme points, coordinates of maximum values ​​and coordinates of minimum values ​​in the signal x(t), and obtain a new sequence of extreme values ​​x 1 (t);

[0073] Step 3: For the extremum sequence x 1 The endpoints of (t) are subjected to symmetrical extension processing to obtain the upper and lower envelopes of the extreme values ​​of the signal, such as figure 2 as shown,

[0074] The process of left endpoint processing is as follows:...

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Abstract

The invention discloses a pipeline defect identification method of suppression-end intrinsic time scale decomposition, which aims at solving the problem that the intrinsic time scale decomposition iseasy for generating an endpoint effect, adopts symmetric extension to process an extremum sequence, and adopts the intrinsic time scale decomposition to process the processed extremum to obtain an intrinsic rotation component. The method comprises the following steps: subtracting the endpoint extension from an original signal, obtaining an intrinsic rotation component, obtaining a novel extremum sequence, repeating the previous steps, obtaining a series of intrinsic rotation components and a single trend item, introducing the endpoint effect evaluation index theta to quantitatively analyze theendpoint effect, and selecting the intrinsic rotation component and the single trend item of a recombinant pipeline scalar magnetic signal by combining kurtosis determination. The recombinant scalarmagnetic signal and the intrinsic rotation component are enveloped, the gradient processing is performed for the enveloped signal, a pipeline deformation index is solved, the frequency spectrum analysis is performed for the recombinant scalar magnetic signal and the intrinsic rotation component, and a pipeline defect is determined by analyzing a gradient abnormal signal and a frequency spectrum analysis result.

Description

technical field [0001] The invention belongs to information detection methods, in particular to a method for identifying defects of buried steel pipelines based on the decomposition of the inherent time scale of the suppression end. Background technique [0002] The environment in which buried steel pipelines are located is complex, and as an important infrastructure of the national economy and people's lives, once an accident occurs, the consequences will be serious. The defects of buried steel pipelines are not easy to observe directly, so magnetic detection, as a non-contact early detection technology for pipeline defects, is of great significance to prolong the service life of pipelines and ensure the smooth progress of industrial production. [0003] Magnetic field detection is a detection method that detects the spontaneous leakage magnetic field signal generated at the defect of the buried steel pipeline, extracts the defect characteristics from it, and then judges th...

Claims

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Application Information

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IPC IPC(8): G01N27/83
CPCG01N27/83
Inventor 王新华齐立夫陈迎春张涛句海洋赵以振潘庆丰
Owner BEIJING UNIV OF TECH
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