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具有低全球变暖潜势制冷剂的制冷系统用于故障检测和诊断的数据集。

Dataset of low global warming potential refrigerant refrigeration system for fault detection and diagnostics.

机构信息

Electrification and Energy Infrastructures Division, Oak Ridge National Laboratory, One Bethel Valley Road, Oak Ridge, TN, 37830, USA.

Computational Sciences and Engineering Division, Oak Ridge National Laboratory, One Bethel Valley Road, Oak Ridge, TN, 37830, USA.

出版信息

Sci Data. 2021 May 27;8(1):144. doi: 10.1038/s41597-021-00927-6.

Abstract

HVAC and refrigeration system fault detection and diagnostics (FDD) has attracted extensive studies for decades; however, FDD of supermarket refrigeration systems has not gained significant attention. Supermarkets consume around 50 kWh/ft of electricity annually. The biggest consumer of energy in a supermarket is its refrigeration system, which accounts for 40%-60% of its total electricity usage and is equivalent to about 2%-3% of the total energy consumed by commercial buildings in the United States. Also, the supermarket refrigeration system is one of the biggest consumers of refrigerants. Reducing refrigerant usage or using environmentally friendly alternatives can result in significant climate benefits. A challenge is the lack of publicly available data sets to benchmark the system performance and record the faulted performance. This paper identifies common faults of supermarket refrigeration systems and conducts an experimental study to collect the faulted performance data and analyze these faults. This work provides a foundation for future research on the development of FDD methods and field automated FDD implementation.

摘要

暖通空调和制冷系统故障检测与诊断(FDD)已经吸引了数十年的广泛研究;然而,超市制冷系统的 FDD 尚未引起足够的重视。超市每年的用电量约为每英尺 50 千瓦时。超市中最大的能源消费者是其制冷系统,它占超市总用电量的 40%-60%,相当于美国商业建筑总能耗的 2%-3%。此外,超市制冷系统也是制冷剂的最大消费者之一。减少制冷剂的使用或使用环保替代品可以带来显著的气候效益。一个挑战是缺乏公开可用的数据集来对系统性能进行基准测试和记录故障性能。本文确定了超市制冷系统的常见故障,并进行了实验研究以收集故障性能数据并分析这些故障。这项工作为未来开发 FDD 方法和现场自动 FDD 实施的研究奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2b2/8159987/f92b16250e6b/41597_2021_927_Fig1_HTML.jpg

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