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BARO algorithm and application in equipment fault diagnosis

It can solve the bottleneck of knowledge acquisition in mechanical equipment fault diagnosis through combining the data mining techniques and the fault diagnosis techniques. This paper presents the bitmap-base association rule optimisation (BARO) algorithm to aim at solving the problems of mining speed slower and the demand of internal memory bigger in association rules mining process. The BARO improves the data structure to reduce the scanning frequency of database and compresses the matrix to reduce the quantity of candidate itemsets in order to improve the speed of equipment fault diagnosis. Based on the BARO algorithm, this paper designs equipment fault diagnosis system.