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Volume 12
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10.3390/buildings12020087
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Article

Construction Theory for a Building Intelligent Operation and Maintenance System Based on Digital Twins and Machine Learning

by
Yuhong Zhao
1,2,
Naiqiang Wang
1,2,
Zhansheng Liu
1,2,* and
Enyi Mu
3
1
College of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
2
The Key Laboratory of Urban Security and Disaster Engineering of the Ministry of Education, Beijing University of Technology, Beijing 100124, China
3
College of Urban and Environmental Sciences, Urban and Economic Geography, Peking University, Beijing 100871, China
*
Author to whom correspondence should be addressed.
Buildings 2022, 12(2), 87; https://doi.org/10.3390/buildings12020087
Submission received: 15 November 2021 / Revised: 15 January 2022 / Accepted: 16 January 2022 / Published: 18 January 2022
(This article belongs to the Collection Cities and Infrastructure)
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Abstract

The operation and maintenance (O&M) of buildings plays an important role in ensuring that the buildings work normally, as well as reducing the damage caused by functional errors. There are obvious problems in the traditional O&M modality, and an effective way to solve them is to make the model smarter. In this paper, a digital twin framework for building operation is proposed, which consists of two key components: a digital twin O&M model and a machine learning algorithm. The process of establishing the digital twin model is introduced in detail, and the method is explained according to the structure, equipment, and energy consumption characteristics of the model. A mechanism of fusing the digital twin and machine learning algorithm is proposed and the prediction process based on an artificial neural network (ANN) is shown. Finally, based on a systematic summary of the modeling process and fusion mechanism, the development path and overall structure of the intelligent O&M system utilizing digital twins is proposed.
Keywords: digital twin; machine learning; artificial neural network; operation and maintenance digital twin; machine learning; artificial neural network; operation and maintenance

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MDPI and ACS Style

Zhao, Y.; Wang, N.; Liu, Z.; Mu, E. Construction Theory for a Building Intelligent Operation and Maintenance System Based on Digital Twins and Machine Learning. Buildings 2022, 12, 87. https://doi.org/10.3390/buildings12020087

AMA Style

Zhao Y, Wang N, Liu Z, Mu E. Construction Theory for a Building Intelligent Operation and Maintenance System Based on Digital Twins and Machine Learning. Buildings. 2022; 12(2):87. https://doi.org/10.3390/buildings12020087

Chicago/Turabian Style

Zhao, Yuhong, Naiqiang Wang, Zhansheng Liu, and Enyi Mu. 2022. "Construction Theory for a Building Intelligent Operation and Maintenance System Based on Digital Twins and Machine Learning" Buildings 12, no. 2: 87. https://doi.org/10.3390/buildings12020087

APA Style

Zhao, Y., Wang, N., Liu, Z., & Mu, E. (2022). Construction Theory for a Building Intelligent Operation and Maintenance System Based on Digital Twins and Machine Learning. Buildings, 12(2), 87. https://doi.org/10.3390/buildings12020087

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