基于设备故障监控的时间序列模式研究应用  

Study and application of time-interval sequential pattern to equipment fault monitoring

作　　者：闫伟[1] 张浩[2] 陆剑峰[1] 

机构地区：[1]同济大学CIMS研究中心,上海200092 [2]上海电力学院电力与自动化工程学院,上海200092

出　　处：《计算机应用》2005年第7期1584-1586,共3页journal of Computer Applications

基　　金：国家863计划项目(2002AA412410)

摘　　要：采用数据挖掘中的时间序列模式对流程企业中的运行数据进行分析,首先采用模糊理论对实际数据进行处理,找出偏离常规运行状态但未到报警界限的参数点,然后采用时间窗对参数离散处理,划分时间间隔得到时间序列数据库。采用TimeSeq_PrefixSpan算法并编程实现,得到了按次序排列且有时间间隔的异常参数点对设备故障影响的规则,起到了对设备故障预警监控的作用。Time-interval sequential pattern mining was used to discover frequent subsequences as patterns from sequence database of flowing industry. Firstly, the large history database were analyzed by fuzzy theory and the exceptional equipment parameters were found. After scattering exceptional parameters by Time-window approach, a new time-interval sequential database was got by dealing with time intervals. In order to find time-interval sequential pattern, TimeSeq_PrefixSpan algorithm is developed from the conventional PrefixSpan algorithm and implemented in flowing industry's production. Then the models can monitor faults when the equipments circulating.

关 键 词：数据挖掘 时间序列分析 TimeSeq_PrefixSpan算法 故障监控 流程企业 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]