EconPapers    
Economics at your fingertips  
 

Development of Fault Diagnosing System for Ice-Storage Air-Conditioning Systems

Ching-Jui Tien, Chung-Yuen Yang, Ming-Tang Tsai and Hong-Jey Gow
Additional contact information
Ching-Jui Tien: Department of Electrical Engineering, Cheng-Shiu University, Kaohsiung 833, Taiwan
Chung-Yuen Yang: Department of Electrical Engineering, Cheng-Shiu University, Kaohsiung 833, Taiwan
Ming-Tang Tsai: Department of Electrical Engineering, Cheng-Shiu University, Kaohsiung 833, Taiwan
Hong-Jey Gow: Kuen-Ling Machinery Refrigerating Co., Ltd., Kaohsiung 826, Taiwan

Energies, 2022, vol. 15, issue 11, 1-13

Abstract: This paper proposes a fault diagnosing system for the Ice-Storage Air-Conditioning System (ISACS) to supervise the operation conditions of the brine chillers. Combining the Radial Basis Function Network (RBFN) and Robust Quality Design (RQD), an Enhanced RBFN (ERBFN) is proposed to pursue fast and accurate fault diagnosis. The RQD method is used to adjust the parameters in the RBFN training stage to improve the searching ability, and good performance with a close spike tracking capability can be seen. The efficiency of the brine chiller in the ISACS was considered as the quality characteristics, the values measured by all instruments were considered as control factors, and noise factors were abnormal variable control factors in the system. ERBFN can improve the efficiency of the ISACS and prevent the equipment from being damaged without warning. ERBFN is used for fault diagnosis to ensure the ISACS performance is normal. Experimental results are provided to show the effectiveness of the proposed method. The new artificial neural network algorithm proposed in this paper was successfully applied to the fault diagnosis of ISACS. It not only provides a reference for enterprises but can also be applied to studies on other topics in the future.

Keywords: ice-storage air-conditioning system; robust quality design; brine chiller; radial basis function network (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/11/3981/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/11/3981/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:11:p:3981-:d:826367

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:15:y:2022:i:11:p:3981-:d:826367