基于Apriori算法的设备故障诊断技术的研究  

Equipment Fault Diagnosis Technology Based on Apriori Algorithm

作　　者：甘超[1] 陆远[1] 李娟[2] 胡莹[1] 

机构地区：[1]南昌大学机电工程学院,南昌330031 [2]中国北方车辆研究所车辆传动重点实验室,北京100072

出　　处：《组合机床与自动化加工技术》2014年第1期100-103,共4页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国家自然科学基金(50905083)

摘　　要：设备故障诊断是设备安全运行的保障,合理分析大量的故障数据能为设备管理提供重要的参考价值。论文采用特征建模技术描述故障设备的特征信息,根据故障数据的特点,以及Apriori算法在故障诊断中应用的瓶颈,采用一种改进的Apriori算法,将故障数据映射为0-1矩阵,根据对矩阵的剪枝和处理计算出故障数据的频繁项集,挖掘多故障之间和故障与运行参数之间的关联关系,为设备管理提供有力支持。最后给出了该方案的可行性实例验证。Equipment fault diagnosis is the safeguard of the safe operation of equipment. Mining massive fault data legitimately provides an important reference for equipment management. Based on the characteristics of fault data and the deficiency of Apriori algorithm using in fault diagnosis, the feature information of faulty equipment is described by feature modeling technology, and an improved Apriori algorithm is proposed. The incidence relation is exhumed among the fault or between the fault and operating parameters by converting fault data to 0 - 1 matrix and calculating the frequent itemsets of fault data by pruning and handling the matrix. A strong support is provided for equipment management. At last an example is given to prove the feasibility.

关 键 词：APRIORI算法 故障诊断 数据挖掘 

分 类 号：TH165.3[机械工程—机械制造及自动化] TG65[金属学及工艺—金属切削加工及机床]