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

Yuhong Zhao,Zhansheng Liu,Naiqiang Wang,Enyi Mu

doi:10.3390/buildings12020087

Yuhong Zhao, Zhansheng Liu + Show 2 more

Open Access

https://doi.org/10.3390/buildings12020087

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Journal: Buildings	Publication Date: Jan 18, 2022
Citations: 31	License type: CC BY 4.0

Affiliation: Beijing University of Technology, Peking University

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.

Highlights

In the process of operating a building, it is difficult to maintain the structures at a safe status all the time, or even in a dangerous state, due to the degradation of materials and damage caused by various harmful factors [1]
The digital twin processes the predictive information analyzed by the machine learning algorithm to make intelligent decisions that are transmitted to physical entities
This paper introduces the idea of digital twin technology for the process of building operation and maintenance, as well as the fusion mechanism of digital twin technology and a machine learning algorithm, to realize the intelligent prediction of building operation and maintenance status

Summary

Introduction

In the process of operating a building, it is difficult to maintain the structures at a safe status all the time, or even in a dangerous state, due to the degradation of materials and damage caused by various harmful factors [1]. As a part of building operation, it is important to conduct maintenance work, such as repairing failures, replacing components, and discovering construction problems—and solving them in time to ensure normal and safe running status [5]. The traditional O&M pattern of buildings has a series of problems, such as data management difficulties, poor measurement and detection accuracy, single technical means, and high cost [6]. Yu et al [7] reported on the importance of BIM technology and analyzed the processes of a digital O&M system. Taffese et al [9]

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