Using an LSTM network to monitor industrial reactors using electrical capacitance and impedance tomography – a hybrid approach

Grzegorz Kłosowski, Tomasz Rymarczyk, Konrad Niderla, Monika Kulisz, Lucasz Skowron, Manuchehr Soleimani

Research output: Contribution to journalArticlepeer-review

18 Citations (SciVal)

Abstract

The article presents a new concept for monitoring industrial tank reactors. The presented concept allows for faster and more reliable monitoring of industrial processes, which increases their reliability and reduces operating costs. The innovative method is based on electrical tomography. At the same time, it is non-invasive and enables the imaging of phase changes inside tanks filled with liquid. In particular, the hybrid tomograph can detect gas bubbles and crystals formed during industrial processes. The main novelty of the described solution is the simultaneous use of two types of electrical tomography: impedance and
capacitance. Another novelty is the use of the LSTM network to solve the tomographic inverse problem. It was made possible by taking the measurement vector as a data sequence. Research has shown that the proposed hybrid solution and the LSTM algorithm work better than separate systems based on impedance or capacitance tomography.
Original languageEnglish
Article number11
JournalEksploatacja i Niezawodność
Volume25
Issue number1
Early online date27 Jan 2023
DOIs
Publication statusPublished - 27 Jan 2023

Keywords

  • LSTM networks
  • electrical tomography
  • industrial systems
  • machine learning
  • process control

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering

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