Title: BARO algorithm and application in equipment fault diagnosis

Authors: QingXiang Zhu; Lei Zhang; Jing Liu

Addresses: College of Economics and Management, Yanshan University, Qinhuangdao, Hebei, 066004, China. ' College of Economics and Management, Yanshan University, Qinhuangdao, Hebei, 066004, China. ' Library, Yanshan University, Qinhuangdao, Hebei, 066004, China

Abstract: 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.

Keywords: equipment faults; fault diagnosis; association rules; a priori algorithms; data mining; optimisation.

DOI: 10.1504/IJMIC.2012.047737

International Journal of Modelling, Identification and Control, 2012 Vol.16 No.3, pp.265 - 271

Published online: 17 Dec 2014 *

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