Automated performance monitoring of HVAC components by artificial intelligence

Authors

  • Maximilian Both Institute of Building Services Engineering | TH Köln | University of Applied Sciences | Germany
  • Nicolai Maisch Institute of Building Services Engineering | TH Köln | University of Applied Sciences | Germany
  • Björn Kämper Institute of Building Services Engineering | TH Köln | University of Applied Sciences | Germany
  • Alina Cartus Institute of Building Services Engineering | TH Köln | University of Applied Sciences | Germany
  • Jochen Müller Institute of Building Services Engineering | TH Köln | University of Applied Sciences | Germany
  • Christian Diedrich Institute of Automation Technology | Otto von Guericke University Magdeburg | Germany

DOI:

https://doi.org/10.34641/clima.2022.144

Keywords:

Industrie 4.0 Interfaces, Natural Language Processing, Energy management systems, Digital twins

Abstract

Energy management systems are an important tool for increasing the energy efficiency of buildings. However, the widespread availability of such systems is offset by the high complexity and high costs of implementation, as well as a lack of data. By using standardized digital twins of technical components, these obstacles can be addressed. In combination with homogeneous semantics of the digital twins and standardized interfaces as uniform access points to the information, the implementation of an energy management system can be simplified. If all technical components of a building have the same information technology structure in the form of digital twins and make their standardized information uniformly available for query, simple query rules can be implemented. These enable the automated integration of the information into an energy management system. However, given the large number of different manufacturers of the technical components, agreement on a common semantic standard in particular seems unlikely. Studies show that methods from the field of Natural Language Processing can be used to process heterogeneous semantics. Agreement on a common vocabulary is no longer necessary. Instead, different semantics can be used and matched to a target vocabulary. In order to use semantic matching in Industrie 4.0 environments, it must be provided as an Industrie 4.0 service. The service provides a translation mechanism from a foreign vocabulary to one's own. For this purpose, a standardized Industrie 4.0 interface consisting of two operations is specified. This interface is implemented prototypically as an API to show how it can be used. The specified interface can be used within the digital twins to process heterogeneous semantics and map them to its own. Extending the Industrie 4.0 approach from homogeneous to heterogeneous semantics can help simplifying the implementation of energy management systems. Simpler implementation lowers the barriers to the use of such systems, which in turn can lead to their higher availability.

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Published

2022-05-14

How to Cite

Both , M. ., Maisch, N. ., Kämper, B. ., Cartus, A. ., Müller, J. ., & Diedrich, C. . (2022). Automated performance monitoring of HVAC components by artificial intelligence. CLIMA 2022 Conference. https://doi.org/10.34641/clima.2022.144

Conference Proceedings Volume

Section

Digitization