Fuel feeding and inhomogeneity of fuel typically cause process fluctuations in the circulating fluidized bed (CFB) process. If control systems fail to compensate the fluctuations, the whole plant will suffer from fluctuations that are reinforced by the closed-loop controls. This phenomenon causes reducing efficiency and the lifetime of process components. Therefore, domain experts are interested in developing tools and techniques for getting better understanding of underlying processes and their mutual dependence in CFB boilers. In this paper we consider an application of data mining (DM) technology to the analysis of time series data from a pilot CFB reactor.
|Title of host publication||Proceedings ECML/PKDD Workshop on PRactical Data Mining (Berlin, Germany, September 22, 2006)|
|Publication status||Published - 2006|