Supermarkets undergo various types of operating faults that can require costly preventive maintenance, service, and repairs. Because supermarkets are growing in number and in the variety of system types and characteristics, information about common faults and equipment is essential prior to investing effort on the development of new fault detection and diagnostics (FDD) methods or other improvements to system design and operation. A study was conducted to investigate supermarket equipment characteristics, such as the prevalence of central vs. distributed systems, condenser types, control strategies, and common operating faults such as refrigerant leakage, failed evaporator or condenser fans, failed compressors, etc. The data come from four sources: expert surveys, facility management system messages, service calls, and service records. Some of the results of the study are that centralized direct expansion systems with on/off compressor capacity control strategy and air-cooled condensers are the most common system types and refrigerant charge problems are the most common source of equipment failure. Case-related problems, in aggregate, are the most frequently occurring faults in supermarkets.

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.

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