Computer IT machine room temperature and humidity sensor is affected by precision air conditioning evaluation method
By using K-MEANS and DBSCAN clustering algorithms to evaluate the impact of precision air conditioning on temperature and humidity sensors in IT data centers, the problems of manual surveying and data labeling were solved. This enabled accurate calculation of the correlation between sensors and air conditioning, as well as the balancing of the temperature field in the data center, thereby reducing air conditioning energy consumption.
CN120408235BActive Publication Date: 2026-07-24NANJING CANATAL DATA CENT ENVIRONMENTAL TECH CO LTD
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Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NANJING CANATAL DATA CENT ENVIRONMENTAL TECH CO LTD
- Filing Date
- 2024-12-03
- Publication Date
- 2026-07-24
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Figure CN120408235B_ABST
Abstract
The application discloses a computer IT machine room temperature and humidity sensor influence evaluation method affected by precision air conditioners, and the basic idea of the application is to change the temperature setting of each air conditioner by a certain step in turn, then acquire the temperature change of all sensors in the machine room in the corresponding period, after the temperature change data is vectorized, the K-MEANS clustering algorithm is used for preliminary grouping clustering to obtain the element density of the clustering subcluster, and the density is used as the clustering radius of the DBSCAN clustering algorithm to perform clustering operation grouping again, so that the influence correlation between each air conditioner and each sensor is acquired, the algorithm does not need manual on-site investigation and data labeling, and can complete the task only through data mining technology, thereby greatly saving the work load.
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