Versatile AHU fault detection – Design, field validation and practical application

Nehasil, Ondřej; Dobiášová, Lucie; Mazanec, Vojtěch; Široký, Ján

doi:10.1016/j.enbuild.2021.110781

Cited by 18 publications

(6 citation statements)

References 42 publications

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“…If-then rules are the best and most commonly used representation for implementing this approach. Table 2 lists examples from selected literature that address the knowledge discovery approach, all of which utilize if-then rules [ 32 , 33 , 34 , 35 , 36 , 37 ].…”

Section: Results Part I: Review and New Classification Of Fdd Approac...mentioning

confidence: 99%

“…The proposed method improves the data reliability and robustness of FDD. On the other hand, Nehasil et al [ 32 ] combined rule-based fault detection with semantic data descriptions and cloud architecture with the goal of creating a general-purpose FDD system. Lin et al [ 34 ] developed and implemented nine algorithms for error correction for HVAC systems.…”

Section: Results Part I: Review and New Classification Of Fdd Approac...mentioning

confidence: 99%

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

Matetić

Štajduhar

Wolf

et al. 2022

Sensors

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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.

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Section: Results Part I: Review and New Classification Of Fdd Approac...mentioning

confidence: 99%

Section: Results Part I: Review and New Classification Of Fdd Approac...mentioning

confidence: 99%

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

Matetić

Štajduhar

Wolf

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…Several faults have been recognized based on the literature review (Zhao et al, 2015(Zhao et al, , 2017Bortolini and Forcada, 2019;Cheng et al, 2020;Alavi et al, 2021;Nehasil et al, 2021;Hosamo et al, 2022b). For example, heating and cooling at the same time, risk of discomfort, heat unexpected on, faulty supply fan, envelope thermal insulation, widows to wall ratio, acoustic attenuator, etc.…”

Section: Classification Of Faults Found In the Literaturementioning

confidence: 99%

“…This is a difficult task, and it becomes considerably more difficult when applied to the context of building systems because the symptoms of faults and the repercussions of those faults are typically not well understood or measured. Recent research has shown an increased interest in the utilization of 'virtual sensors,' which provide estimations of values that are not directly quantifiable (Ferretti et al, 2015;Mattera et al, 2018;Nehasil et al, 2021;Zhang et al, 2021;Chen J. et al, 2022;Zhang and Leach, 2022). Even though it can be challenging or expensive to measure specific parameters and values directly, indirect measurements and analytical approaches have made it possible to develop tools that are more effective in terms of their cost-effectiveness in estimating degradation signals and current conditions.…”

Section: Recent Researchmentioning

confidence: 99%

A review of the Digital Twin technology for fault detection in buildings

Hosamo

Nielsen

Alnmr

et al. 2022

Front. Built Environ.

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This study aims to evaluate the utilization of technology known as Digital Twin for fault detection in buildings. The strategy consisted of studying existing applications, difficulties, and possibilities that come with it. The Digital Twin technology is one of the most intriguing newly discovered technologies rapidly evolving; however, some problems still need to be addressed. First, using Digital Twins to detect building faults to prevent future failures and cutting overall costs by improving building maintenance is still ambiguous. Second, how Digital Twin technology may be applied to discover inefficiencies inside the building to optimize energy usage is not well defined. To address these issues, we reviewed 326 documents related to Digital Twin, BIM, and fault detection in civil engineering. Then out of the 326 documents, we reviewed 115 documents related to Digital Twin for fault detection in detail. This study used a qualitative assessment to uncover Digital Twin technology’s full fault detection capabilities. Our research concludes that Digital Twins need more development in areas such as scanner hardware and software, detection and prediction algorithms, modeling, and twinning programs before they will be convincing enough for fault detection and prediction. In addition, more building owners, architects, and engineers need substantial financial incentives to invest in condition monitoring before many of the strategies discussed in the reviewed papers will be used in the construction industry. For future investigation, more research needs to be devoted to exploring how machine learning may be integrated with other Digital Twin components to develop new fault detection methods.

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“…Before CFD simulation, it is critical to mesh the computational domain into suitable grids. Since the target bedroom has a simple structure, this paper decides to mesh the empty and occupied areas separately into a few structured grids [9] (Figure 3).…”

Section: Meshingmentioning

confidence: 99%

Influence of Air Supply Height on Sleep Comfort Through Computational Fluid Dynamics Simulation

Gao¹,

Shang²,

Xia³

et al. 2021

IJHT

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Taking the bed in the bedroom as an air-conditioning system (ACS), this paper attempts to disclose the influence of air supply height (ASH) on sleep comfort. Specifically, a computational fluid dynamics (CFD) model was established to simulate the air temperature distribution, air speed, and carbon dioxide content (CDC) indoor at five ASHs of the ACS. The simulation results were compared with lab data. On this basis, the aeration efficiency (AE), temperature regulation risk (TRR), and energy-use factor (EUF) of the ACS were analyzed under different working conditions, and the overall efficacy of the ACS was assessed comprehensively by the technique for order of preference by similarity to ideal solution (TOPSIS).

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Versatile AHU fault detection – Design, field validation and practical application

Cited by 18 publications

References 42 publications

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

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

A review of the Digital Twin technology for fault detection in buildings

Influence of Air Supply Height on Sleep Comfort Through Computational Fluid Dynamics Simulation

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