Reliability prediction method for cooling equipment of data centers and 5 G base stations based on regional failure
The field failure data of cooling equipment used in the data center and 5 G base station in different installation areas were analyzed.The maximum likelihood method was used to establish the life distribution model.The optimal fitting of the life distribution conformed to the three parameter of Weibull distribution,and the fault recurrence con-formed to the non-homogeneous Poisson process.There was significant difference in the reliability of regional clustering.Reliability predictions are made for typical area failure data based on repairable and non repairable systems,and the predicted results based on re-pairable systems have good correlation with actual maintenance data.The established life distribution,fault recurrence,and reliability prediction method based on regional failures is suitable for data analysis of external failures of cooling equipment used in data centers and 5 G base stations,as well as fault prediction and development of maintenance spare parts and repair strategies.
data centers5 G base stationscooling equipmentregional classificationthree parameters of weibull distributionnonhomogeneous poisson processreliability pre-diction