Mining Delay in Streaming Time Series of Industrial Process

Haijie Gu, Gang Rong

Abstract: Time delay is a general phenomenon in industrial process. Accurate evaluation on delay is important in data preprocessing when mine manufactory process data. As typical streaming time series, sensors’ data of industrial process have attracted much attention recently. A new concept , trend similarity search, is proposed based on raw monotony between two industrial process variables. The new concept is for those two time series which are similar only in trend but dissimilar in shape, whereas similarity search may not do well in such condition. An algorithm DelayMine is also proposed to mine delay between two interrelated time series by trend similarity search. Moreover, the DelayMine is extended to online algorithm for processing streaming time series. The properties and performance of DelayMine is demonstrated through experiments both on systems with steady and time-varying delay.