A theoretical investigation of modelling the temperature measurement in oil pipelines with edge devices. (15th January 2021)

• Record Type: Journal Article
• Authors: Huan, Huiting; Liu, Lixian; Huan, Binglian; Chen, Xiaolong; Zhan, Jinsong; Liu, Qiang
• Is Part Of: Measurement. Volume 168(2021)
• Publication Date: 2021-01-15
• Subjects: Temperature prediction -- Edge device -- Green's function -- Boundary-equivalent method; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2020.108440
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: Comprehensive model and guidelines for pipeline temperature measurement. Green's functions of cylindrical and rectangular pipes in all scenarios. The idea of boundary-equivalent diffusion model for composite pipes. Edge device precisely predicts internal temperature within short period. Abstract: The temperature measurement performed by edge devices is effective in remote pipeline monitoring and maintenance in an Internet of Things (IoT) network. It provides a non-invasive, easy-to-install and compatible solution for upgrading existing pipelines. However, there is no systematic testing scheme for different pipelines. This article presents comprehensive theories and simulation results for indirect temperature measurement in pipeline. The basic heat transfer models in cylindrical and rectangular pipes were established. Analytical solutions which are applicable for embedded devices at the edge were proved to have good accuracy as conventional methods realized at the server. The model interpreted temperature evolution inside the pipe for both convective and conductive condition. We also proposed an effective approach to model multilayer non-metallic pipelines with boundary-equivalent single-layer approximation. The temperature field was determinable by an embedded system using a dichotomy algorithm. This work aims to provide guidelines for non-invasive time-dependent temperature measurement in IoT pipeline applications.