Name File Type Size Last Modified
  1SX 05/25/2020 08:36:AM
  2OH 05/25/2020 08:37:AM
  3MF 05/25/2020 08:38:AM
  4CF 05/25/2020 08:39:AM
  5EB 05/25/2020 08:40:AM

Project Description

Summary:  View help for Summary 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.



Related Publications

Published Versions

Export Metadata

Report a Problem

Found a serious problem with the data, such as disclosure risk or copyrighted content? Let us know.

This material is distributed exactly as it arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.