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Log information produced from the use of equipment has seen exponential growth with the increasing of the complexity and informatization of equipments. Universal log file reprocessing rules and critical information extracting adaptor are developed through analysis for massive log files of a certain type of equipment, while equipment health managing system is constructed based on data mining algorithm and evaluation for equipment health is realized based on cloud barycenter assessment method. The system can extract valuable information from massive log files and accelerate the location of equipment anomaly, thus can improve problem solving efficiency. It can also realize equipment health warning by configuring critical parameters and monitor threshold.