Publication: Frost detection and defrost control: emerging trends, methods, and experimental evaluations
| dc.contributor.coauthor | Hassan, H. | |
| dc.contributor.coauthor | Malik, A. N. | |
| dc.contributor.coauthor | Nawaz, T. | |
| dc.contributor.coauthor | Elahi, H. | |
| dc.contributor.department | Department of Mechanical Engineering | |
| dc.contributor.department | MARC (Manufacturing and Automation Research Center) | |
| dc.contributor.kuauthor | Lazoğlu, İsmail | |
| dc.contributor.kuauthor | Ur Rahman, Hammad | |
| dc.contributor.kuauthor | Akbar, Hassan | |
| dc.contributor.schoolcollegeinstitute | Research Center | |
| dc.contributor.schoolcollegeinstitute | College of Engineering | |
| dc.date.accessioned | 2026-08-14T11:23:36Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | Frost buildup on evaporator surfaces significantly reduces heat transfer efficiency in refrigeration systems, undermining overall performance. Effective frost detection and defrost control are therefore critical for maintaining optimal operation. This paper presents a comprehensive review of recent advancements in frost detection and defrosts control. It covers various defrosting mechanisms, including active and passive approaches, and classifies defrost control strategies into direct (sensor-based) and indirect types. Furthermore, it compares traditional sensor-based methods with emerging image processing techniques and advanced AI-driven solutions. An experimental evaluation of these methods highlights their relative strengths and limitations. Finally, the study identifies key research gaps, particularly in the integration of advanced sensing technologies for precise frost detection and defrost control. | |
| dc.description.harvestedfrom | Manual | |
| dc.description.indexedby | WOS | |
| dc.description.indexedby | Scopus | |
| dc.description.publisherscope | International | |
| dc.description.readpublish | N/A | |
| dc.description.sponsoredbyTubitakEu | N/A | |
| dc.description.sponsorship | The Department of Mechatronics Engineering at the College of Electrical and Mechanical Engineering (CEME) , National University of Sciences and Technology (NUST) , provided support for this study. Data utilized for the experimental evaluation was collected at the Manufacturing and Automation Research Center, Department of Mechanical Engineering, Koc University, Istanbul, Turkey. Furthermore, the authors would like to thank BEKO Global in Istanbul, Turkey, for providing the refrigerator for data acquisition. | |
| dc.description.version | Published Version | |
| dc.identifier.ScopusPercentile | 82 | |
| dc.identifier.ScopusQuartile | Q1 | |
| dc.identifier.WoSPercentile | 78 | |
| dc.identifier.WoSQuartile | Q1 | |
| dc.identifier.doi | 10.1016/j.ijrefrig.2025.08.005 | |
| dc.identifier.eissn | 1879-2081 | |
| dc.identifier.embargo | N/A | |
| dc.identifier.endpage | 141 | |
| dc.identifier.issn | 0140-7007 | |
| dc.identifier.scopus | 2-s2.0-105012760161 | |
| dc.identifier.startpage | 121 | |
| dc.identifier.uri | http://doi.org/10.1016/j.ijrefrig.2025.08.005 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14288/34449 | |
| dc.identifier.volume | 179 | |
| dc.identifier.wos | 001579145400001 | |
| dc.keywords | Frost detection | |
| dc.keywords | Defrost control | |
| dc.keywords | Artificial intelligence | |
| dc.keywords | Digital image processing | |
| dc.language | eng | |
| dc.publisher | Elsevier | |
| dc.relation.affiliation | Koç University | |
| dc.relation.collection | Koç University Institutional Repository | |
| dc.relation.ispartof | International Journal of Refrigeration | |
| dc.relation.openaccess | N/A | |
| dc.rights | N/A | |
| dc.rights.uri | N/A | |
| dc.subject | Thermodynamics | |
| dc.subject | Engineering | |
| dc.title | Frost detection and defrost control: emerging trends, methods, and experimental evaluations | |
| dc.type | Journal Article | |
| dspace.entity.type | Publication | |
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