Thermal images of the server in different running status
Principal Investigator(s): View help for Principal Investigator(s) hang liu, Dalian University of Technology
Version: View help for Version V2
Name | File Type | Size | Last Modified |
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CSV_file | 05/25/2020 08:50:AM | ||
thermal_image | 05/25/2020 08:24:AM |
Project Citation:
liu, hang. Thermal images of the server in different running status. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-05-26. https://doi.org/10.3886/E119603V2
Project Description
Summary:
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Balancing the uneven temperature distribution of data centers can reduce cooling energy consumption significantly,
as the overheated surface of servers is one of the root causes of the uneven distribution. This paper
presents a method for intelligently diagnosing server operating status based on the heat distribution of the server
surface. Five types of server operation can be diagnosed: normal status, main fan failure, vice-fan failure, air vent
blockage and low-load status. The method involves signal processing and pattern recognition techniques such as
thermal image enhancement, region segmentation and image classification. First, thermal images of server
outlets in running status are captured as data; second, the images are preprocessed for standardization; third,
after homomorphic filtering enhancement, the images are subjected to one-dimensional maximum entropy
segmentation to obtain server hotspot images; fourth, morphological features, texture features and statistical
features are extracted from hotspot images; finally, the server status is diagnosed by a support vector machine.
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