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Pipelines used in the petrochemical industries are an essential means of transporting materials economically, efficiently and safely. However, ferromagnetism can lead to cracking, corrosion and other defects due to operation, wear, stress and accidental damage. Moreover, because the pipelines work under the condition of high pressure and for long periods of time, if these defects cannot be discovered and repaired quickly, it will cause problems leading to lower transport efficiency, leaks and other issues. Most pipelines are built under the sea or underground, in the event there are some troubles, the repair cost will be very high. Magnetic flux leakage (MFL) is the most common technique used in pipeline inspection at present 1 . In this technique 2 , the wall of the pipelines is magnetised axially to near saturation flux density. If, at some point, the thickness of the wall is reduced by a defect, a higher fraction of the magnetic flux will ‘leak’ from the wall into the air inside and outside the pipe. The magnetic leakage field measured on the near side of the pipe contains information about the pipe condition. Then the identification of the defect can be implemented based on MFL signals by analysing the correlation between MFL signals and the defect geometry parameter
Ji et al. (Thu,) studied this question.