Recommended by the IIR / IIR document
Use of artificial intelligence in the refrigeration field.
Number: 2061
Author(s) : CITARELLA B., MAURO A. W., PELELLA F.
Summary
Nowadays more than 5 billion of refrigeration and air-conditioning units are employed worldwide. Internet of Things technology is becoming widely used also in these applications. Operational data can be collected from units installed worldwide and used to train artificial intelligence (AI) tools and black box digital twins. These models can predict energy consumption or detect fault and inefficiencies, allowing a timely intervention on the unit before a total lack of cold occur. In this paper a state-of-the-art review regarding the implementation of AI in refrigeration sector is presented. Works are classified according to the following topics: machine learning tools for fault detection and diagnosis (FDD), black box digital twin to predict energy consumption and performances, AI application for demand defrost, optimization algorithms for complex system.
Available documents
Format PDF
Pages: 8
Available
Public price
20 €
Member price*
Free
* Best rate depending on membership category (see the detailed benefits of individual and corporate memberships).
Details
- Original title: Use of artificial intelligence in the refrigeration field.
- Record ID : 30028931
- Languages: English
- Subject: Technology
- Source: 6th IIR Conference on Thermophysical Properties and Transfer Processes of Refrigerants
- Publication date: 2021/09/01
- DOI: http://dx.doi.org/10.18462/iir.TPTPR.2021.2061
- Document available for consultation in the library of the IIR headquarters only.
Links
See other articles from the proceedings (48)
See the conference proceedings
Indexing
-
Themes:
Energy efficiency, energy savings;
Industrial, commercial and domestic refrigeration: general information - Keywords: Review; Optimization; Artificial intelligence; Prediction; Machine learning; Energy consumption; Performance; Defrosting; Artificial neural network; COP; Refrigeration; Air conditioning; Failure; Control (automatic)
-
Application of artificial intelligence to refri...
- Author(s) : CERDÁN CARTAGENA, PÉREZ GOMARIZ, LÓPEZ GÓMEZ A.
- Date : 2022/04
- Languages : English
- Source: XI Congreso Ibérico y IX Congreso Iberoamericano de Ciencias y Técnicas del Frío, CYTEF 2022.
- Formats : PDF
View record
-
Frost detection with neural networks: determini...
- Author(s) : KLINGEBIEL J., SALOMON P., VERING C., MÜLLER D.
- Date : 2023/05/15
- Languages : English
- Source: 14th IEA Heat Pump Conference 2023, Chicago, Illinois.
- Formats : PDF
View record
-
Parallel deep neural network for scalable coupl...
- Author(s) : CHEN S., LIU Z., CHEN K., ZHU X., JIN X., DU Z.
- Date : 2023/08/21
- Languages : English
- Source: Proceedings of the 26th IIR International Congress of Refrigeration: Paris , France, August 21-25, 2023.
- Formats : PDF
View record
-
Energy saving pre-cooling pattern search of an ...
- Author(s) : YOON M. S., YOON W. S.
- Date : 2021/08/31
- Languages : English
- Source: 13th IEA Heat Pump Conference 2021: Heat Pumps – Mission for the Green World. Conference proceedings [full papers]
- Formats : PDF
View record
-
Model-free HVAC control in buildings: a review.
- Author(s) : MICHAILIDIS P., MICHAILIDIS I., VAMVAKAS D., KOSMATOPOULOS E.
- Date : 2023/10
- Languages : English
- Source: Energies - vol. 16 - 20
- Formats : PDF
View record