Automated fault detection and diagnosis methods for supermarket equipment (RP-1615). (17th November 2017)

• Record Type: Journal Article
• Authors: Behfar, Alireza; Yuill, David; Yu, Yuebin
• Is Part Of: Science and technology for the built environment. Volume 23:Number 8(2017)
• Page Start: 1253
• Page End: 1266
• Publication Date: 2017-11-17
• Subjects: Heating -- Periodicals; Ventilation -- Periodicals; Air conditioning -- Periodicals; Refrigeration and refrigerating machinery -- Periodicals; Indoor air quality -- Periodicals; Indoor air quality; Air conditioning; Heating; Refrigeration and refrigerating machinery; Ventilation; Periodicals; 697
• DOI: 10.1080/23744731.2017.1333352
• Languages: English
• ISSNs: 2374-474X

Abstract

Abstract : Many automated fault detection and diagnostics methods have been developed for application to building mechanical systems over the past 20 years because they have the potential to reduce operating costs and energy consumption by providing early warning of performance degradation faults. Supermarkets could be a very beneficial setting to deploy automated fault detection and diagnostics, particularly in the refrigeration systems, which are major energy users and are known to commonly suffer from significant refrigerant leakage problems. The current article provides an overview of the common mechanical systems deployed in supermarkets, and then describes a comprehensive review of the literature on automated fault detection and diagnostics methods from other systems that could potentially be applied in supermarket settings. A collection of supermarket field data is analyzed in the context of its potential use in automated fault detection and diagnostics methods from other systems. The review includes methods to categorize and assess the automated fault detection and diagnostics approaches, from the perspective of a potential adopter of automated fault detection and diagnostics technology for a supermarket setting. The article concludes that supermarket automated fault detection and diagnostics is still in the early stages of development and that there is a need to further develop automated fault detection and diagnostics methods for supermarket applications. To facilitate the development of supermarket-specific automated fault detection and diagnostics approaches, additional data sets from refrigeration equipment are needed.