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Pipeline In-Line Inspection Method, Instrumentation and Data Management.
Ma, Qiuping; Tian, Guiyun; Zeng, Yanli; Li, Rui; Song, Huadong; Wang, Zhen; Gao, Bin; Zeng, Kun.
Afiliación
  • Ma Q; School of Automation, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • Tian G; School of Automation, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • Zeng Y; School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK.
  • Li R; Shenyang Academy of Instrumentation Science, Shenyang 110043, China.
  • Song H; PipeChina Northern Company, Langfang 065000, China.
  • Wang Z; Shenyang Academy of Instrumentation Science, Shenyang 110043, China.
  • Gao B; School of Automation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.
  • Zeng K; School of Automation, University of Electronic Science and Technology of China, Chengdu 611731, China.
Sensors (Basel) ; 21(11)2021 Jun 03.
Article en En | MEDLINE | ID: mdl-34205033
ABSTRACT
Pipelines play an important role in the national/international transportation of natural gas, petroleum products, and other energy resources. Pipelines are set up in different environments and consequently suffer various damage challenges, such as environmental electrochemical reaction, welding defects, and external force damage, etc. Defects like metal loss, pitting, and cracks destroy the pipeline's integrity and cause serious safety issues. This should be prevented before it occurs to ensure the safe operation of the pipeline. In recent years, different non-destructive testing (NDT) methods have been developed for in-line pipeline inspection. These are magnetic flux leakage (MFL) testing, ultrasonic testing (UT), electromagnetic acoustic technology (EMAT), eddy current testing (EC). Single modality or different kinds of integrated NDT system named Pipeline Inspection Gauge (PIG) or un-piggable robotic inspection systems have been developed. Moreover, data management in conjunction with historic data for condition-based pipeline maintenance becomes important as well. In this study, various inspection methods in association with non-destructive testing are investigated. The state of the art of PIGs, un-piggable robots, as well as instrumental applications, are systematically compared. Furthermore, data models and management are utilized for defect quantification, classification, failure prediction and maintenance. Finally, the challenges, problems, and development trends of pipeline inspection as well as data management are derived and discussed.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Transportes / Manejo de Datos Tipo de estudio: Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2021 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Transportes / Manejo de Datos Tipo de estudio: Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2021 Tipo del documento: Article País de afiliación: China