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.

To solve the problems of high maintenance cost, low reusability and poor scalability of in-pipe inspection data analysis system, an in-pipe inspection data analysis system based on REST (Representational State Transfer) architecture is designed and implemented. A multilayer service-oriented architecture based on REST is designed, which decouples the functions of client, middleware, server and data storage to improve the maintainability of the software. REST APIs (Application Program Interfaces) based on HTTP (Hypertext Transfer Protocol) are designed, which encapsulate the core functions such as data analysis, signal processing, automatic identification and quantization into language and platform independent services to meet the needs of multiuser, cross platform and online data analysis. An adaptation method of in-line inspection tool based on metadata is designed, which abstracts the in-line inspection tool into a separate metadata file and decouples it from the client and server programs to improve the scalability of the software. Practice has proved the architecture can improve the maintainability, reusability and scalability of the software, and provide a basis for constructing online in-pipe inspection data analysis service based cloud.