Device and method for adaptive filtering of pipeline magnetic flux leakage signal

Abstract

The invention relates to a self-adaptive filtering device and method for pipeline magnetic leakage signals. The self-adaptive filtering device comprises a data collector, a conditioning circuit, an A / D converter, a data collection controller and a data processor. The self-adaptive filtering method includes the steps that (1), the pipeline magnetic leakage signals are collected; (2), the pipeline magnetic leakage signals are classified based on a correlation region growth algorithm; (3), feature points of the pipeline defect magnetic leakage signals are extracted; (4), the pipeline defect magnetic leakage signals are filtered; (5) data compensation based on the feature points is performed on the pipeline defect magnetic leakage signals; (6), based on a sliding average value algorithm, the normal magnetic leakage signals are filtered; (7), the complete pipeline magnetic leakage signals are reconstructed and output. The defects that according to a common filtering method, the filtering time is long and the feature points are misplaced are overcome, efficiency and precision of signal classification are improved, and the speed of feature point extraction is increased.

Description

technical field [0001] The invention belongs to the technical field of non-destructive testing, and relates to an adaptive filtering device and method for pipeline magnetic flux leakage signals. Background technique [0002] With the gradual lengthening of oil and gas pipelines at home and abroad and the gradual increase of transportation volume, the efficient and safe transportation of oil and gas pipelines has received extensive attention. Due to long-term corrosion, wear and accidental mechanical damage, various defects will be formed in ferromagnetic oil and gas pipelines. In order to prevent leakage accidents, it is necessary to use a pipeline detection device to detect pipelines. [0003] The magnetic flux leakage testing method is one of the main methods of non-destructive testing. It is aimed at ferromagnetic materials with high permeability such as pipelines, which are magnetized, and the magnetic force lines are bent and deformed at the defect, and some of the mag...

AI Technical Summary

Problems solved by technology

However, due to the influence of the field environment and the ferromagnetic surface conditions inside the tested pipeline, the signals collected by the magnetic flux leakage detection method often have a lot of noise attached to the detection signals, and the direct use of defect identification will seriously affect the correctness of the detection results. , therefore, it is necessary to use a suitable filtering method to process the magnetic flux leakage signal

Since pipeline magnetic flux leakage detection generally adopts an online detection system, the length of the detected pipeline can reach tens of kilometers, and the collected data of magnetic flux leakage signals is huge. The common filtering method lacks pertinence in the processing of magnetic flux leakage signals, so the filtering time is long , and the filtered signal feature points are easily misplaced, which affects the judgment of the shape and size of the defect

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