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Substation Signal Matching with a Bagged Token Classifier

  • Qin Wang
  • Sandro Schönborn
  • Yvonne-Anne Pignolet
  • Theo Widmer
  • Carsten Franke
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10868)

Abstract

Currently, engineers at substation service providers match customer data with the corresponding internally used signal names manually. This paper proposes a machine learning method to automate this process based on substation signal mapping data from a repository of executed projects. To this end, a bagged token classifier is proposed, letting words (tokens) in the customer signal name vote for provider signal names. In our evaluation, the proposed method exhibits better performance in terms of both accuracy and efficiency over standard classifiers.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Qin Wang
    • 1
  • Sandro Schönborn
    • 2
  • Yvonne-Anne Pignolet
    • 2
  • Theo Widmer
    • 3
  • Carsten Franke
    • 2
  1. 1.ETH ZürichZürichSwitzerland
  2. 2.ABB Corporate ResearchBadenSwitzerland
  3. 3.ABB Power Grid - Grid AutomationBadenSwitzerland

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