Intelligent analysis system using magnetic flux leakage data in pipeline inner inspection

US11488010B2 · kind B2 · utility

Assignee

• Northwestern University · US

Inventors

• Jin LIU · Shenyang, CN
• Ming Fu · Beijing, CN
• Sen Lu · Shenyang, CN
• Hua Zhang · Shenyang, CN
• Da zhong Ma · Shenyang, CN
• Gang Wang · Shenyang, CN
• Jian Feng · Shenyang, CN
• Xin Zhang · Laiyang City, CN
• Ge Yu · Longbeilingcun, CN
• Hong WEI · Shenyang, CN

Key dates

• Filing date: Feb 13, 2019
• Grant date: Nov 1, 2022
• Expiry date: Nov 9, 2040

Classification

• Technology area (CPC G): Physics
• CPC primary: G06Q10/20
• WIPO field: Measurement
• WIPO sector: Instruments

Abstract

Provided is an intelligent analysis system for inner detecting magnetic flux leakage (MFL) data in pipelines, including a complete data set building module, a discovery module, a quantization module and a solution module, wherein: a complete data set building method is adopted in the complete data set building module to obtain a complete magnetic flux leakage data set; a pipeline connecting component discovery method is adopted in the discovery module to obtain the precise position of a weld; an anomaly candidate region search and identification method is adopted in the discovery model to find out magnetic flux leakage signals with defects; a defect quantization method based on a random forest is adopted in the quantization module to obtain a defect size; and a pipeline solution based on an improved ASME B31G standard is adopted in the solution module to output an evaluation result.