Estimation of moisture variations on paper machines

An improved estimation algorithm for use in processing data generated online by a scanning sensor is described. The algorithm is to be used as part of a paper machine control system to maintain the moisture content of the sheet at a target value. The algorithm makes use of a previously published model to rapidly estimate, in the presence of noise, cross-direction and machine-direction (CD and MD) moisture profiles. The basic algorithm consists of a modified least-squares (LS) parameter identifier for estimating CD profile deviations and a Kalman filter for estimating MD disturbances. Simulation results showing the effectiveness of the algorithm in estimating known profiles are given. Results of the offline application of the algorithm to industrial data are also given. Online tests have been performed to demonstrate the improvements in accuracy and speed of detection of process upsets. The algorithm can be extended to other measurement models