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Low charge detection and diagnoses for non-critically charged refrigeration system

Authors: Amro Quedan; Fadi Alsaleem; Mark Gariety; Paul Fullenkamp;

Low charge detection and diagnoses for non-critically charged refrigeration system

Abstract

In this paper, a new set of algorithms has been developed to detect low charge fault for single compressor non-critically charged refrigeration system for both frozen and perishable goods. A mix of field units' data and experimental data were used to build the detection algorithms. Multiple detection algorithms were devised based on the operation modes. The system operates in multiple distinctive modes. Each mode has a defining characteristic. The used data includes several healthy and predefined low charge defected systems which gave us a prediction of the loss of charge percentage in different operational modes. This prediction provides us with a good knowledge of the system performance and operation.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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