Automatic fault detection and diagnosis in refrigeration systems, A data-driven approach

Zahra Soltani

doi:10.54337/aau535542944

Automatic fault detection and diagnosis in refrigeration systems, A data-driven approach

Zahra Soltani

Publikation: Ph.d.-afhandling

118 Downloads (Pure)

Originalsprog	Engelsk
Vejledere	Leth, John-Josef, Hovedvejleder
Eksterne samarbejdspartnere	BITZER Electronics A/S
Udgiver	Aalborg Universitetsforlag
ISBN'er, elektronisk	978-87-7573-742-0
DOI	https://doi.org/10.54337/aau535542944
Status	Udgivet - 2023

Bibliografisk note

PhD supervisor:
Associate Professor John-Josef Leth, Aalborg University

Adgang til dokumentet

10.54337/aau535542944

PHD_ZSForlagets udgivne version, 14,8 MB

AUB Link

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2 Konferenceartikel i proceeding
1 Tidsskriftartikel

Fault detection and diagnosis in refrigeration systems using machine learning algorithms
Soltani, Z., Sørensen, K. K., Leth, J. & Bendtsen, J. D., dec. 2022, I: International Journal of Refrigeration. 144, s. 34-45 12 s.
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

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13 Citationer (Scopus)

198 Downloads (Pure)
Robustness analysis of PCA-SVM model used for fault detection in supermarket refrigeration systems
Soltani, Z., Kjaer Soerensen, K., Leth, J-J. & Bendtsen, J. D., 2021, 2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE). Kuala Lumpur, Malaysia: IEEE, 6 s.
Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

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2 Citationer (Scopus)

73 Downloads (Pure)
Fault Detection of Supermarket Refrigeration Systems Using Convolutional Neural Network
Soltani, Z., Soerensen, K. K., Leth, J. & Bendtsen, J. D., 18 okt. 2020, IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society. IEEE Computer Society Press, s. 231-238 8 s. 9254485. (Proceedings of the Annual Conference of the IEEE Industrial Electronics Society).
Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

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3 Citationer (Scopus)

109 Downloads (Pure)

Citationsformater

@misc{4dedbd630bd64a0eb4f539208d59e71e,

title = "Automatic fault detection and diagnosis in refrigeration systems, A data-driven approach",

keywords = "machine learning, fault detection, classification, refrigeration, SVM, LDA, PCA, CNN, data-driven",

author = "Zahra Soltani",

note = "PhD supervisor: Associate Professor John-Josef Leth, Aalborg University",

year = "2023",

doi = "10.54337/aau535542944",

language = "English",

series = "Ph.d.-serien for Det Tekniske Fakultet for IT og Design, Aalborg Universitet",

publisher = "Aalborg Universitetsforlag",

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AU - Soltani, Zahra

N1 - PhD supervisor: Associate Professor John-Josef Leth, Aalborg University

PY - 2023

Y1 - 2023

KW - machine learning

KW - fault detection

KW - classification

KW - refrigeration

KW - SVM

KW - LDA

KW - PCA

KW - CNN

KW - data-driven

U2 - 10.54337/aau535542944

DO - 10.54337/aau535542944

M3 - PhD thesis

T3 - Ph.d.-serien for Det Tekniske Fakultet for IT og Design, Aalborg Universitet

PB - Aalborg Universitetsforlag

ER -

Automatic fault detection and diagnosis in refrigeration systems, A data-driven approach

Bibliografisk note

Adgang til dokumentet

AUB Link

Publikation

Fault detection and diagnosis in refrigeration systems using machine learning algorithms

Robustness analysis of PCA-SVM model used for fault detection in supermarket refrigeration systems

Fault Detection of Supermarket Refrigeration Systems Using Convolutional Neural Network

Citationsformater