Research on Abnormal Identification of HVAC Operation in Data Centers Based on Decision Tree
In order to reduce the noise in the identification results of HVAC operational anomalies,a decision tree algorithm was introduced to design and study a method for identifying HVAC operational anomalies,taking a certain data center as an example.By sensing the operating conditions of HVAC through tools such as sensors,instruments,and monitoring systems,the data center can collect and preprocess HVAC operating data based on this.Transform and integrate data from different formats and sources to achieve metadata feature extraction and category division based on decision trees.Perform spatial clustering on data of the same category to achieve data clustering and abnormal data recognition.The results show that using the designed method to identify abnormal operation of HVAC in data centers can control the noise in the identification results to a relatively low value.
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