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Applicable Predictive Maintenance Diagnosis Methods in Service-Life Prediction of District Heating Pipes

Pakdad Pourbozorgi Langroudi*, Ingo Weidlich

*Korrespondierende/r Autor/-in für diese Arbeit

Abstract

Maintaining the supply chain in every industry is an important concern for the operators. The negative impacts of inappropriate maintenance could be discussed from different perspectives as well as capital loss, reputation loss, hazard and risk for lives, etc. In recent years, District heating (DH) in the countries that employing this technology broadly, turned to a vital energy infrastructure for delivering heat from suppliers to the consumers. Therefore, the reliability of the system is of high importance for the public interest. The transition from reactive maintenance to proactive maintenance have improved a lot the reliability to the system. Currently, many industries are exploiting different forms of artificial intelligence (AI) to predict the failures and plan for interventions to increase the system efficiency. In this paper the different methods of predictive maintenance have been reviewed and the compatibility to apply on a DH network has been discussed.

OriginalspracheEnglisch
Seiten (von - bis)294-304
Seitenumfang11
FachzeitschriftEnvironmental and Climate Technologies
Jahrgang24
Ausgabenummer3
DOIs
PublikationsstatusVeröffentlicht - 1 Nov. 2020

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

  1. SDG 07 – Erschwingliche und saubere Energie
    SDG 07 – Erschwingliche und saubere Energie

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