Pipeline magnetic flux leakage testing on-line data compression method

Abstract

The invention provides a pipeline magnetic flux leakage testing on-line data compression method mainly used for compressing mass data in pipeline magnetic flux leakage on-line testing, and belongs to the field of signal processing. The method comprises the following steps that (1) detected magnetic flux leakage data are divided into data segments having the same number of bytes; (2) whether each data segment contains pipeline defect information is judged by means of average absolute deviation statistical magnitude, and only the data segments containing the defect information are stored; (3) if multiple data segments contain a large amount of redundant signal data, main content of the data segments is analyzed, and only the first little main content is stored; (4) integral promotion wavelet decomposition is conducted on each detecting signal of each data segment after two-stage compression, threshold processing is conducted on wavelet coefficients produced after decomposition, then adaptive coding is conducted on the processed wavelet coefficients, and finally only bit stream data after corresponding coding are stored. Therefore, the method can achieve high-efficiency compression of pipeline magnetic flux leakage testing on-line data.

Description

technical field [0001] The invention relates to an online data compression method for pipeline magnetic flux leakage detection, which uses various technologies in three stages to effectively compress massive pipeline magnetic flux leakage detection data to reduce the requirement for data storage capacity of pipeline detectors, and belongs to the field of signal processing. Background technique [0002] Pipelines are the main way of energy transportation. With the continuous expansion of energy demand, the construction of long-distance oil and gas pipelines is still accelerating. More than 70% of the pipelines currently in use in my country have been in operation for close to or more than 20 years. These pipelines will form various defects due to corrosion, wear, mechanical damage and other reasons during the years of use. Because pipelines work under high pressure for a long time, if these defects are not found and repaired in time, they will eventually lead to pipeline leak...

AI Technical Summary

Problems solved by technology

However, the key to successfully detecting pipeline defect information is to be able to obtain high-quality magnetic flux leakage signal data, but high-quality signal data requires detectors with hig

Images