Automated Horizontal Slurry Flow Regime Recognition Using Statistical Analysis of the ERT Signal

Yousef Faraj, Mi Wang, Jiabin Jia

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Flow regime recognition is not only useful for characterisation of the flow, but also for the purpose of modeling, system controls and optimization and correction of flow regime dependent flow meters. This paper proposes a new indirect method for on-line recognition of the active horizontal slurry flow regime using statistical signal analysis of measurements obtained with a high performance Electrical Resistance Tomography system (ERT). Significant features of the ERT signal are extracted from both time domain and frequency domain. A set of experiments were carried out using a pilot-scale slurry flow loop, through which a mixture of sand and tap water was pumped into a 50 mm inner-diameter test section. All common slurry flow regimes are considered in the recognition scheme, including the transitional regime boundaries covering the transport velocity range of 1.5-5 m/s. Two types of sand are used in the experiments, medium (75-900 μm) and coarse (150-2200 μm), each with different throughput volumetric concentration, 2% and 10%. 1.2 m transparent pipe section was included into the test section, so as to visually inspect the prevailing flow regime and capture photographic images of the flow. A code was developed not only to render the recognition of the active flow regime, but also to visualise the distribution of the solid particles across the pipe cross-section and display the mean solids volume fraction. The evaluation of the proposed recognition method suggests 90.32% successful rate.
Original languageEnglish
Pages (from-to)821-830
Number of pages10
JournalProcedia Engineering
Publication statusPublished - 10 Apr 2015

Keywords / Materials (for Non-textual outputs)

  • Electrical Resistance Tomography, horizontal slurry flow, slurry flow regime recognition., ERT signal analysis


Dive into the research topics of 'Automated Horizontal Slurry Flow Regime Recognition Using Statistical Analysis of the ERT Signal'. Together they form a unique fingerprint.

Cite this