Analysis And Improvement Of Life Prediction And Health Management Algorithm For Cooling Fan

Duo to its low price and high performance,cooling fan is widely used in cooling systemof electrolic equipment. The working efficiency of the cooling system is directly dependent onwhether fan running state is in good condition.So cooling fan is a key facter which affects theresidual life of electrolic equipment.cooling fan’s performance has a direct impact on theperformance of expensive equipments such as telecommunications equipment, power supplyand server.Therefore, research on the life prediction and health management of cooling fan issignificant.Paper first briefs the failure modes and failure mechanisms of cooling fan and carried outa seris of work. Then select the measure parameters according to the fan structure, workingprinciple, operating parameters of cooling fan. The life prediction algorithm of cooling fan aredevided into three parts, including environment module,electronic module and mechanicalmodule, then make an improvement of the electronic module basis on the existingalgorithm.But this three parts just predict the residual life of cooling fan, then waveletanalysis of vibration signals to failure prediction is also raised. In addition, summarizingexperience data based on the large number of failure experiments in this study and making areaserch on the relationship between the anomal datas and failure type.Finally make datafusion based on the four modules to predict the failure mode and health conditions and givea appropriate maintenance program. The proposed algorithm of this paper is proved to beeffective after a lot of fan failure experiments.