L
Lijuan Wang
Researcher at University of Kent
Publications - 56
Citations - 723
Lijuan Wang is an academic researcher from University of Kent. The author has contributed to research in topics: Rotational speed & System of measurement. The author has an hindex of 13, co-authored 51 publications receiving 469 citations. Previous affiliations of Lijuan Wang include North China Electric Power University.
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Application of soft computing techniques to multiphase flow measurement: A review
TL;DR: A comprehensive review of the soft computing techniques for multiphase flow metering with a particular focus on the measurement of individual phase flowrates and phase fractions is presented.
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Rotational Speed Measurement Through Electrostatic Sensing and Correlation Signal Processing
TL;DR: The principle and application of electrostatic sensors and correlation signal processing techniques to real-time measurement of rotational speed and the results suggest that the distance between the electrodes and the surface of the rotating object is a key factor affecting the performance of the measurement system.
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Gas-Liquid Two-Phase Flow Measurement Using Coriolis Flowmeters Incorporating Artificial Neural Network, Support Vector Machine, and Genetic Programming Algorithms
TL;DR: Data driven models that are incorporated into Coriolis flowmeters to measure both the liquid mass flowrate and the gas volume fraction of a two-phase flow mixture suggest that the SVM models are superior to the BP-ANN, RBF, and GP models for two- phase flow measurement in terms of robustness and accuracy.
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Harnessing the power of machine learning for carbon capture, utilisation, and storage (CCUS) – a state-of-the-art review
Yongliang Yan,Yongliang Yan,Tohid N. Borhani,Sai Gokul Subraveti,Kasturi Nagesh Pai,Vinay Prasad,Arvind Rajendran,Paula Nkulikiyinka,Jude Odianosen Asibor,Zhien Zhang,Ding Shao,Lijuan Wang,Wenbiao Zhang,Yong Yan,William Ampomah,Junyu You,Junyu You,Meihong Wang,Edward J. Anthony,Vasilije Manovic,Peter T. Clough +20 more
TL;DR: In this paper, the main steps of the CCUS value chain (CO2 capture, transport, utilisation, storage) and explore how ML is playing a leading role in expanding the knowledge across all fields of CCUS.
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Electrostatic sensors – Their principles and applications
TL;DR: A comprehensive review of the electrostatic sensors and sensing systems that have been developed for the measurement and monitoring of a range of process variables and conditions, and their signal conditioning electronics, signal processing methods as well as possible new applications are discussed.