期刊
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
卷 200, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ijpvp.2022.104803
关键词
PIG; Wax-deposition; Wax-removal; Wax-layer identification; Deep-learning
资金
- National Natural Science Foundation of China [52104054]
This paper introduces a novel PIG and its pigging scheme, highlighting its innovative features and motion control mechanism. Furthermore, an intelligent wax-removal algorithm based on Convolutional Neural Network is proposed and its superiority is demonstrated, laying the foundation for future practical applications.
In a previous paper, a novel PIG is reported, and in this paper, more elements are given and a Deep-learning technology-based pigging scheme is proposed. The PIG mainly consists of a speed-control unit and a wax -removal unit which are connected by a couple of Hook joints. It differentiates itself from the previous proposal by outstanding features including measuring arms, turbine generator, etc. The realization of jetting, cutting, and bypass valve-based motion control mechanism is elaborated. To overcome the disadvantages of traditional wax-removal methods and improve the processing efficiency, a new intelligent wax-removal algorithm based on Convolution Neural Network is proposed to realize a real-time identification of different wax layer thickness. In addition, the training results of the Convolution Neural Network method are compared with some other traditional machine-learning algorithms to prove its superiority, and it lays a foundation for the practical pigging application in the future.
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