Two-dimensional reproduction method for petroleum pipeline defects through least squares support vector machines (LS-SVM)

A technology of support vector machine and least squares, applied in the pipeline system, mechanical equipment, gas/liquid distribution and storage, etc., can solve the problems of complex inverse problem and large amount of calculation, achieve online reconstruction and improve convergence accuracy , to solve the effect of slow training

Inactive Publication Date: 2013-09-25
HARBIN ENG UNIV
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Problems solved by technology

The inverse problem is very complicated, and a commonly used method to solve the inverse problem is to use an iterative method, but this method is computationally intensive

Method used

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  • Two-dimensional reproduction method for petroleum pipeline defects through least squares support vector machines (LS-SVM)
  • Two-dimensional reproduction method for petroleum pipeline defects through least squares support vector machines (LS-SVM)
  • Two-dimensional reproduction method for petroleum pipeline defects through least squares support vector machines (LS-SVM)

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Experimental program
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Embodiment

[0047] The process of predicting the geometric parameters of defects according to the magnetic flux leakage signals generated by defects is essentially a process of establishing the mapping relationship between magnetic flux leakage signals and geometric parameters of defects.

[0048] (1) The measured values ​​of MFL signals and defects collected from actual pipelines are used as experimental data for network training after preprocessing such as denoising and normalization. There are 90 sets of sample data, the first 80 sets are used as training data, the last 10 sets are used as test data, and each set of data has 120 sampling points.

[0049] (2) Set the least squares support vector machine parameters: kernel function parameter σ and penalty factor γ. The magnetic flux leakage signal is used as the input of the least squares support vector machine, and the defect contour (length and depth) is used as the output.

[0050] Use the least squares support vector machine for two...

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Abstract

The invention relates to two-dimensional reproduction methods for petroleum pipeline defects, particularly to a two-dimensional reproduction method for petroleum pipeline defects through LS-SVM. The two-dimensional reproduction method comprises the steps of taking actually measured pipeline magnetic flux leakage signal data and pipeline defects data as experimental data for pipeline defect reconstruction after denoising and normalization processing; taking magnetic flux leakage signals as input and defect profiles containing lengths and widths as output, and determining training sample numbers and a kernel function parameter sigma and a penalty factor gamma; taking pipeline magnetic flux leakage signal data L as output by using a trained LS-SVM model, and performing two-dimensional defect reconstruction on pipelines by using the pipeline magnetic flux leakage signals to reproduce pipeline defect profiles. According to the two-dimensional reproduction method, the calculation process is greatly simplified, the convergence precision is improved, and on-line reconstruction and accurate reproduction of the pipelines can be achieved.

Description

technical field [0001] The invention relates to a two-dimensional reappearance method for oil pipeline defects, in particular to a two-dimensional reappearance method for oil pipeline defects by a least square support vector machine. Background technique [0002] With the rapid development of my country's oil and natural gas industry, pipeline transportation has become the main way of my country's land oil and gas transportation. However, with the increase of pipe age, construction defects, man-made damage, corrosion and other reasons, pipeline accidents occur frequently, causing major economic losses, seriously polluting the environment and even endangering the lives of production personnel. Magnetic flux leakage detection technology is the most widely used method in pipeline defect detection. It uses the principles of magnetic flux leakage and ray detection, and without affecting normal production, through the intelligent detector walking in the pipeline, the damage of oil...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): F17D5/02
Inventor 傅荟璇刘胜张红梅王宇超赵凯岐陈明杰郑秀丽刘洪丹
Owner HARBIN ENG UNIV
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