Fault detection and diagnosis of air-conditioning system using long short-term memory recurrent neural network

• Autorzy: Sulaiman Noor Asyikin , Menanti Nur Amalina Sabal , Yusop Azdiana Md , Zainudin Muhammad Noorazlan Shah , Yatim Norhidayah Mohamad , Razak Norazlina Abd , Abdullah Md Pauzi

Identyfikatory

DOI

10.15199/48.2023.09.21

Warianty tytułu

PL

Wykrywanie usterek i diagnostyka układu klimatyzacji z wykorzystaniem powtarzającej się sieci neuronowej z pamięcią długookresową

• Języki publikacji: EN

Abstrakty

EN

In this project, a fault detection and diagnosis (FDD) system was developed using Long Short-Term Memory Recurrent Neural Network (LSTM RNN), to detect and classify six common faults in a centralised chilled water air conditioning system. Datasets from a lab-scale centralised chilled water air conditioning system were used in the developed model. Results showed that the classifier model demonstrated a classification accuracy of over 99.3% for all six classes.

PL

W ramach tego projektu opracowano system wykrywania i diagnozowania usterek (FDD) z wykorzystaniem powtarzającej się sieci neuronowej długookresowej pamięci (LSTM RNN) w celu wykrycia i sklasyfikowania sześciu powszechnych usterek w scentralizowanym systemie klimatyzacji wody lodowej. W opracowanym modelu wykorzystano zestawy danych ze scentralizowanego systemu klimatyzacji wody lodowej w skali laboratoryjnej. Wyniki pokazały, że model klasyfikatora wykazał dokładność klasyfikacji na poziomie ponad 99,3% dla wszystkich sześciu klas.

Słowa kluczowe

EN

chilled water system; fault detection; LTSM-RNN

PL

system wody lodowej; diagnostyka usterek; wykrywanie usterek; LTSM-RNN

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2023
• Tom: R. 99, nr 9
• Strony: 113--117
• Opis fizyczny: Bibliogr. 20 poz., rys., tab.

Twórcy

autor

Sulaiman Noor Asyikin

• Centre for Telecommunication Research & Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia

• https://orcid.org/0000-0003-3126-7309

autor

Menanti Nur Amalina Sabal

• Mybrush Industries, Lot 210, Jalan Seelong, 81400 Senai, Johor, Malaysia

autor

Yusop Azdiana Md

• Centre for Telecommunication Research & Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia

• https://orcid.org/0000-0002-1864-1952

autor

Zainudin Muhammad Noorazlan Shah

• Centre for Telecommunication Research & Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia

• https://orcid.org/0000-0001-5621-9632

autor

Yatim Norhidayah Mohamad

• Centre for Telecommunication Research & Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia

• https://orcid.org/0000-0002-6464-8354

autor

Razak Norazlina Abd

• Centre for Telecommunication Research & Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia

autor

Abdullah Md Pauzi

• Centre of Electrical Energy Systems (CEES), School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), 81310 Skudai, Johor, Malaysia

• https://orcid.org/0000-0002-8357-731X

Bibliografia

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