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Machine Learning Based Predictive Maintenance of Infrastructure Facilities in the Cryolithozone

  • Andrey V. TimofeevEmail author
  • Viktor M. Denisov
Chapter
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 255)

Abstract

This chapter provides some practical aspects and peculiarities of the use of Machine Learning based Predictive Maintenance for the infrastructure facilities in the cryolithozone. Some mathematical models of Machine Learning based Predictive Maintenance are described, which have shown their practical effectiveness. The solutions of several important problems of Predictive Maintenance for pipelines located in cryolithozone are considered, including: problem of leak detection from pipelines taking into account the possible damage to the pipeline foundation due melting of permafrost; problem of automatic classifying of defects that led to leaks; problem of prompt corrosion spot detection in the pipelines as well as problem of identifying the current state of the corrosion process in the pipeline. The problem of optimizing the procedure for incident tickets processing in the Predictive Maintenance system for oil pipelines was also considered.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.LLP “EqualiZoom”AstanaKazakhstan
  2. 2.“Flagman Geo” Ltd.Saint-PetersburgRussia

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