A robust fault detection and diagnosis strategy for multiple faults of VAV air handling units

Wang, Haitao; Chen, Youming

doi:10.1016/j.enbuild.2016.06.013

Cited by 50 publications

(26 citation statements)

References 34 publications

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“…Heating coil stuck related faults in different working modes: ODhc,damp aa) Mixing air humidity sensor errors: Hair,mix bb) Cooling coil stuck related faults: ODcc,damp [160] SPcomR (including APAR rules)…”

Section: ) Theoretical Deduction Analysis (Tda)mentioning

confidence: 99%

Review on Fault Detection and Diagnosis Feature Engineering in Building Heating, Ventilation, Air Conditioning and Refrigeration Systems

Liu

et al. 2021

IEEE Access

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Section: ) Theoretical Deduction Analysis (Tda)mentioning

confidence: 99%

Review on Fault Detection and Diagnosis Feature Engineering in Building Heating, Ventilation, Air Conditioning and Refrigeration Systems

Liu

et al. 2021

IEEE Access

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“…Syiam [7] developed a neural expert system to diagnoses early eye diseases of patient. The developed system based on the patient signs and symptoms, and uses the multiplayer feed forward networks with a single hidden layer [8]. In addition, an expert system is a computer program that stores the specific experts' knowledge and experience to solve problems or giving advice.…”

Section: Expert Systemmentioning

confidence: 99%

A Fault Diagnosis Expert System for Commercial Bus Manufacturing process

Nian¹,

Fai²

2018

IJET

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Bus manufacturing is one of the important assets in automotive industries as well as mode of public transportation. The design process is difficult and long throughout time. Moreover, there are many manuals, rules and regulation according to different standard which make the standardization and design process to be difficult and time consuming. Hence, this project describes the use of an expert system shell for commercial bus design. In bus manufacturing field, design of commercial bus is heavily depending on human experts. With the help of expert system, process of design commercial bus will be shortened up to 56.5% compared to conventional way. The developed system can be used as a training module for inexperienced personnel. In this research work, the fault diagnosis system was developed by using Kappa-PC expert system shell. It is supported by object orientated technology for the MS window environment. Lastly, the developed system will be validated with a case study to verify the capability of the developed system.

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“…The third-stage deals with proposing an importance ranking of the diagnosed faults in terms of their urgency for health, productivity, comfort, and energy use [22]. [7,[25][26][27][28][29][30][31][32][33][34][35][36][37] Valve stuck closed [7, 25-31, 33, 34, 36, 38] Valve stuck partially open [7, 25-29, 31, 33, 36, 38-44] Leaky valve [7, 19, 25-27, 29, 31-34, 36, 39, 43, 45, 46] Unstable valve control [28,29,31,36,47] Undersized coil [26,36] Coil fouling [26,29,33,36,40,43,46]…”

Section: Literature Reviewmentioning

confidence: 99%

“…Supply air temperature bias [7, 19, 25-27, 30, 32, 37, 40, 44, 51, 57-70] Return air temperature bias [7,25,26,37,40,48 Table 1 lists the AHU and VAV faults studied in the literature in the past 20 years. The vast majority of the previous research efforts have been dedicated to diagnosing physical faults in the AHUs.…”

Section: Ahu Sensorsmentioning

confidence: 99%

Characterization of a building's operation using automation data: A review and case study

Gunay

Shen

Yang

2017

Building and Environment

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Vous avez des questions?Nous pouvons vous aider. Pour communiquer directement avec un auteur, consultez la première page de la revue dans laquelle son article a été publié afin de trouver ses coordonnées. Si vous n'arrivez pas à les repérer, communiquez avec nous à PublicationsArchive-ArchivesPublications@nrc-cnrc.gc.ca.Abstract: This paper presents a critical review of the automated on-going commissioning (AOGC) methods for air-handling units (AHU) and variable air volume terminal (VAV) units in commercial buildings. The common faults studied in the literature were identified. The diagnostic approaches taken and the characteristics of the fault-symptom datasets utilized were categorized. It was found that the diagnostics methods were vastly fragmented, and most of them employed pure-statistical approaches. Only a few studies attempted to assimilate the automation data within the underlying physical processes. In addition, a large fraction of the reviewed literature has been devoted to physical faults in AHUs. Only a few studies were conducted to diagnose faults-related with controls programming and faults at the zone level. Upon the literature survey findings, an inverse greybox modelling-based AOGC approach was put forward. Its strengths and weaknesses were demonstrated through a case study conducted using the archived building automation system (BAS) data of an office building in Ottawa, Canada. The results of this case study indicate that inverse greybox modelling-based AOGC is a promising method to diagnose both physical and controls programming related faults at AHUs and VAVs.

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A robust fault detection and diagnosis strategy for multiple faults of VAV air handling units

Cited by 50 publications

References 34 publications

Review on Fault Detection and Diagnosis Feature Engineering in Building Heating, Ventilation, Air Conditioning and Refrigeration Systems

Review on Fault Detection and Diagnosis Feature Engineering in Building Heating, Ventilation, Air Conditioning and Refrigeration Systems

A Fault Diagnosis Expert System for Commercial Bus Manufacturing process

Characterization of a building's operation using automation data: A review and case study

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