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An intelligent system to monitor refrigeration devices
Author(s) -
Kužnar Damjan,
Piltaver Rok,
Gradišek Anton,
Gams Matjaž,
Luštrek Mitja
Publication year - 2017
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/exsy.12199
Subject(s) - computer science , refrigeration , task (project management) , alarm , quality (philosophy) , component (thermodynamics) , embedded system , artificial intelligence , machine learning , real time computing , systems engineering , mechanical engineering , philosophy , materials science , physics , epistemology , engineering , composite material , thermodynamics
Refrigeration systems have been a vital component of our lives for more than a century. Apart from storing food, they are used to store sensitive goods such as pharmaceutical products or reactive chemicals. The deterioration of the refrigeration system performance due to aging or malfunction directly affects the quality of stored goods. Therefore, an early detection of deviation in performance is an important task. This paper presents a system that monitors operation of refrigeration devices and alerts the user to possible irregularities in the operation run. The emphasis is on recognition of gradual changes of performance that indicate upcoming hardware problems. The system consists of 2 modules: human‐defined expert rules and machine learning. The machine‐learning module learns to recognize abnormal behaviour of devices automatically. Furthermore, it can distinguish between different abnormal events and allow the user to classify some of the types as normal, so that they not longer raise an alarm. The machine learning was evaluated by comparing its recognition of abnormal events and classification accuracy of such events to the performance of a human operator. The system can in principle be adapted to any electronic device that periodically applies some system for sustaining a predefined quality (e.g., temperature).