A Review of Data-Driven Approaches and Techniques for Fault Detection and Diagnosis in HVAC Systems

Heating, ventilation, and air conditioning (HVAC) systems are a popular research topic because buildings’ energy is mostly used for heating and/or cooling. These systems heavily rely on sensory measurements and typically make an integral part of the smart building concept. As such, they require the...

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Published inSensors (Basel, Switzerland) Vol. 23; no. 1; p. 1
Main Authors Matetić, Iva, Štajduhar, Ivan, Wolf, Igor, Ljubic, Sandi
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 20.12.2022
MDPI
Subjects
Air Conditioning
Air Pollution, Indoor - analysis
Analysis
Buildings
data-driven approach
Electric fault location
Energy consumption
Energy efficiency
fault detection and diagnosis
Heating
HVAC
HVAC equipment
HVAC systems
Literature reviews
Methods
Reliability (Engineering)
Review
Systematic review
Trends
Ventilation
Croatia
HVAC systems
fault detection and diagnosis
data-driven approach
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Abstract Heating, ventilation, and air conditioning (HVAC) systems are a popular research topic because buildings’ energy is mostly used for heating and/or cooling. These systems heavily rely on sensory measurements and typically make an integral part of the smart building concept. As such, they require the implementation of fault detection and diagnosis (FDD) methodologies, which should assist users in maintaining comfort while consuming minimal energy. Despite the fact that FDD approaches are a well-researched subject, not just for improving the operation of HVAC systems but also for a wider range of systems in industrial processes, there is a lack of application in commercial buildings due to their complexity and low transferability. The aim of this review paper is to present and systematize cutting-edge FDD methodologies, encompassing approaches and special techniques that can be applied in HVAC systems, as well as to provide best-practice heuristics for researchers and solution developers in this domain. While the literature analysis targets the FDD perspective, the main focus is put on the data-driven approach, which covers commonly used models and data pre-processing techniques in the field. Data-driven techniques and FDD solutions based on them, which are most commonly used in recent HVAC research, form the backbone of our study, while alternative FDD approaches are also presented and classified to properly contextualize and round out the review.
AbstractList Heating, ventilation, and air conditioning (HVAC) systems are a popular research topic because buildings’ energy is mostly used for heating and/or cooling. These systems heavily rely on sensory measurements and typically make an integral part of the smart building concept. As such, they require the implementation of fault detection and diagnosis (FDD) methodologies, which should assist users in maintaining comfort while consuming minimal energy. Despite the fact that FDD approaches are a well-researched subject, not just for improving the operation of HVAC systems but also for a wider range of systems in industrial processes, there is a lack of application in commercial buildings due to their complexity and low transferability. The aim of this review paper is to present and systematize cutting-edge FDD methodologies, encompassing approaches and special techniques that can be applied in HVAC systems, as well as to provide best-practice heuristics for researchers and solution developers in this domain. While the literature analysis targets the FDD perspective, the main focus is put on the data-driven approach, which covers commonly used models and data pre-processing techniques in the field. Data-driven techniques and FDD solutions based on them, which are most commonly used in recent HVAC research, form the backbone of our study, while alternative FDD approaches are also presented and classified to properly contextualize and round out the review.
Heating, ventilation, and air conditioning (HVAC) systems are a popular research topic because buildings' energy is mostly used for heating and/or cooling. These systems heavily rely on sensory measurements and typically make an integral part of the smart building concept. As such, they require the implementation of fault detection and diagnosis (FDD) methodologies, which should assist users in maintaining comfort while consuming minimal energy. Despite the fact that FDD approaches are a well-researched subject, not just for improving the operation of HVAC systems but also for a wider range of systems in industrial processes, there is a lack of application in commercial buildings due to their complexity and low transferability. The aim of this review paper is to present and systematize cutting-edge FDD methodologies, encompassing approaches and special techniques that can be applied in HVAC systems, as well as to provide best-practice heuristics for researchers and solution developers in this domain. While the literature analysis targets the FDD perspective, the main focus is put on the data-driven approach, which covers commonly used models and data pre-processing techniques in the field. Data-driven techniques and FDD solutions based on them, which are most commonly used in recent HVAC research, form the backbone of our study, while alternative FDD approaches are also presented and classified to properly contextualize and round out the review.Heating, ventilation, and air conditioning (HVAC) systems are a popular research topic because buildings' energy is mostly used for heating and/or cooling. These systems heavily rely on sensory measurements and typically make an integral part of the smart building concept. As such, they require the implementation of fault detection and diagnosis (FDD) methodologies, which should assist users in maintaining comfort while consuming minimal energy. Despite the fact that FDD approaches are a well-researched subject, not just for improving the operation of HVAC systems but also for a wider range of systems in industrial processes, there is a lack of application in commercial buildings due to their complexity and low transferability. The aim of this review paper is to present and systematize cutting-edge FDD methodologies, encompassing approaches and special techniques that can be applied in HVAC systems, as well as to provide best-practice heuristics for researchers and solution developers in this domain. While the literature analysis targets the FDD perspective, the main focus is put on the data-driven approach, which covers commonly used models and data pre-processing techniques in the field. Data-driven techniques and FDD solutions based on them, which are most commonly used in recent HVAC research, form the backbone of our study, while alternative FDD approaches are also presented and classified to properly contextualize and round out the review.
Audience Academic
Author Wolf, Igor
Matetić, Iva
Štajduhar, Ivan
Ljubic, Sandi
AuthorAffiliation 2 Center for Artificial Intelligence and Cybersecurity, University of Rijeka, R. Matejcic 2, HR-51000 Rijeka, Croatia
1 Faculty of Engineering, University of Rijeka, Vukovarska 58, HR-51000 Rijeka, Croatia
AuthorAffiliation_xml – name: 1 Faculty of Engineering, University of Rijeka, Vukovarska 58, HR-51000 Rijeka, Croatia
– name: 2 Center for Artificial Intelligence and Cybersecurity, University of Rijeka, R. Matejcic 2, HR-51000 Rijeka, Croatia
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  surname: Wolf
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  surname: Ljubic
  fullname: Ljubic, Sandi
BackLink https://www.ncbi.nlm.nih.gov/pubmed/36616600$$D View this record in MEDLINE/PubMed
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fault detection and diagnosis
data-driven approach
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Snippet Heating, ventilation, and air conditioning (HVAC) systems are a popular research topic because buildings’ energy is mostly used for heating and/or cooling....
Heating, ventilation, and air conditioning (HVAC) systems are a popular research topic because buildings' energy is mostly used for heating and/or cooling....
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SubjectTerms Air Conditioning
Air Pollution, Indoor - analysis
Analysis
Buildings
data-driven approach
Electric fault location
Energy consumption
Energy efficiency
fault detection and diagnosis
Heating
HVAC
HVAC equipment
HVAC systems
Literature reviews
Methods
Reliability (Engineering)
Review
Systematic review
Trends
Ventilation
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Title A Review of Data-Driven Approaches and Techniques for Fault Detection and Diagnosis in HVAC Systems
URI https://www.ncbi.nlm.nih.gov/pubmed/36616600
https://www.proquest.com/docview/2761203777
https://www.proquest.com/docview/2761983710
https://pubmed.ncbi.nlm.nih.gov/PMC9824457
https://doaj.org/article/7e542f5f32e54f4383ba2a003523741a
Volume 23
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