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

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.

Optimization of the Geometric Parameters of the Thermal Insulation of the Heating System by Using Multi-Pipe Circular Thermal Insulation

“…Authors noted the need of government support, through regulations and financial aids, that could increase efficiency of solutions. Pourbozorgi Langroudi et al [5] reviewed different methods of predictive maintenance and the compatibility to apply on a DH network. Al-Barqawi and Zayed [6] classified three main groups of factors influencing DHN efficiency changes in time as: physical factors connected with pipes (like age material, diameter, isolation etc.)…”