基于云计算环境下Apriori算法的设备故障诊断技术研究  

Equipment Fault Diagnosis Technology Based on Apriori Algorithm in Cloud Computing Environment

作　　者：邱昕[1] 甘超[1] 江雄心[1] 涂海宁[1] 顾嘉[1] 

机构地区：[1]南昌大学机电工程学院,南昌330031

出　　处：《组合机床与自动化加工技术》2014年第4期45-48,共4页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国家自然科学基金(50905083)

摘　　要：故障诊断是保障设备安全运行的重要手段。文章采用结构化存储的故障数据模型,考虑到故障数据的特点,以及传统Apriori算法的瓶颈,提出了一种改进的Apriori算法,应用于MapReduce计算框架,减少了算法的扫描次数,提高了算法的执行效率。在云计算环境下对故障数据进行关联规则挖掘,找出发生故障时各设备检测状态的关联关系,为设备维修和管理提供可靠依据。最后给出了该方法的可行性实例验证。Equipment fault diagnosis is an important means to ensure safe operation of equipment. Structured storage of the fault data model is used in this paper. And an improved Apriori algorithm is proposed accord- ing to the characteristics of fault data and the deficiency of Apriori algorithm, combining the MapReduce programming model, which reduces the number of scanning and improves the efficiency of the algorithm. The correlation is exhumed among equipment inspection status by mining the association rules of fault data in cloud computing environment, which provides reliable support for equipment maintenance and management. At last an example is given to prove the feasibility.

关 键 词：云计算 故障诊断 数据挖掘 APRIORI算法 

分 类 号：TH166[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]