With the rapid development of the "Micro Cooling Fan" IT and microelectronics technology, the heat flux density electronic devices continues to increase, the power consumption is increasing, electronic equipment toward lighter, thinner direction, so that the electronic device cooling problems becoming more and more prominent. Cooling fan as a critical component of electronic equipment cooling system, plays a vital role in the smooth ensure reliable operation. According to statistics, most of the mechanical cooling fan failure focused on the bearing failure. Therefore, the "Micro Cooling Fan" bearing fault diagnosis and condition assessment undertaken to effectively ensure the reliability of electronic equipment operation and extend the life of electronic devices. Run for the vibration mechanism and bearing cooling fan, it carried out a series of fault diagnosis and research status assessment, "Micro Cooling Fan" The main contents include: analysis of the structural characteristics of the cooling fan, recalled the rolling bearing and vibration mechanism signal characteristics; the use of EMD decomposition, wavelet analysis, AR since the vibration signal MED regression linear prediction and filtering, signal processing techniques to analyze the cooling fan bearings to achieve a cooling fan bearing fault diagnosis; at the same time, we construct a special comb shaped filter, the signal from the frequency domain to establish a health index, bearing on the health status monitoring; In addition, the paper also uses SVM technology to operational status cooling fan bearings are classified and identified and classified based on the results of the structure degradation index cooling fan bearings to achieve a cooling fan bearing degradation assessment.