Magnetic flux leakage (MFL) detection is one of the most popular methods of pipeline inspection. It is a nondestructive testing technique which uses magnetic sensitive sensors to detect the magnetic leakage field of defects on both the internal and external surfaces of pipelines. This paper introduces the main principles, measurement and processing of MFL data. As the key point of a quantitative analysis of MFL detection, the identification of the leakage magnetic signal is also discussed. In addition, the advantages and disadvantages of different identification methods are analyzed. Then the paper briefly introduces the expert systems used. At the end of this paper, future developments in pipeline MFL detection are predicted.

With the significant increase in demand for artificial intelligence, environmental map reconstruction has become a research hotspot for obstacle avoidance navigation, unmanned operations, and virtual reality. The quality of the map plays a vital role in positioning, path planning, and obstacle avoidance. This review starts with the development of SLAM (Simultaneous Localization and Mapping) and proceeds to a review of V-SLAM (Visual-SLAM) from its proposal to the present, with a summary of its historical milestones. In this context, the five parts of the classic V-SLAM framework—visual sensor, visual odometer, backend optimization, loop detection, and mapping—are explained separately. Meanwhile, the details of the latest methods are shown; VI-SLAM (Visual inertial SLAM) is reviewed and extended. The four critical techniques of V-SLAM and its technical difficulties are summarized as feature detection and matching, selection of keyframes, uncertainty technology, and expression of maps. Finally, the development direction and needs of the V-SLAM field are proposed.

The transportation of hydrogen is a weak link in the large‐scale development of the hydrogen energy industry. Injecting hydrogen into the natural gas pipeline network for transportation is an efficient way to achieve the large‐scale, long‐distance, and low‐cost transportation of hydrogen. Hydrogen can lead to hydrogen embrittlement in natural gas pipelines and cause safety incidents if hydrogen and natural gas are not mixed uniformly. Therefore, it is necessary to study the blending process and blending uniformity of hydrogen and natural gas. In this study, a three‐dimensional model of the hydrogen‐injected natural gas pipeline was constructed. The effects of hydrogen injection inlet and turbulator configuration on the mixing process of hydrogen and natural gas were investigated using a computational fluid dynamics approach. The results show that increasing the number of hydrogen injection inlets shortens the distance L_98% of uniform mixing of hydrogen and natural gas. Increasing the radial distance r from the initial hydrogen mixing positions to the center of the pipeline will shorten the distance for uniform gas mixing in the pipeline. The addition of turbulator configurations in the pipeline significantly reduces the distance to uniform gas mixing. Changing the distance L_turb from the turbulator to the initial mixing position further shortens the distance between hydrogen and natural gas mixing uniformly. The results of this study provide a reference for the structural design of the hydrogen–natural gas mixing pipeline and the gas distribution state during the mixing process.

Hydrogen is a clean energy source with high combustion calorific value and nonpolluting products. However, the high transportation costs hinder the development of hydrogen energy. A high flow rate, long-distance, and high-efficiency delivery can be realized by mixing natural gas with hydrogen, which significantly reduces the transportation cost. However, high concentrations of hydrogen aggregates risks hydrogen embrittlement in the natural-gas pipeline network and leakage. An injector is a highly efficient gas-blending device. Therefore, analyzing and optimizing the multiple structural parameters of the injector are necessary for improving the mixing efficiency and homogeneity of hydrogen and natural gas. First, eight structural parameters of the injector were selected and four levels were considered for each parameter. Subsequently, an orthogonal experiment table was constructed using the orthogonal experimental method. Finally, a modeling simulation was performed using Fluent simulation software. The results showed that the injectors can significantly shorten the distance of mixing uniformity and achieve faster mixing uniformity. The diameter of the mixing pipe was found to be the main factor affecting the overall score. Computational Fluid Dynamic-20 (CFD-20) had the highest overall score. The LCOV10% for CFD-20 improved by 21.5% over that of the initial model, and the composite score improved from 0.93 to 0.98. The results can provide a reference for the design of injector parameters and installation of metering equipment.