Open Collections

Estimation and identification of moisture content in paper

University of British Columbia

The purpose of this thesis is to summarize some results obtained for an improved moisture estimation and identification algorithm which extracts, the cross direction (CD) moisture profiles and machine direction (MD) moisture variations from the composite measured profile, in the presence of noise. The objective is to use the algorithm as part of a paper machine control system to maintain the moisture content of the sheet at a target value and keep a uniform cross-sectional profile shape. The estimation and identification scheme is based upon a nonlinear model, and consists of a modified least squares algorithm for estimating cross direction profile deviations and a Kalman filter for estimating machine direction variations and disturbances. The scheme, when tested on simulated data where the true profiles are known, is shown to give robust and effective results. Off-line testing of the algorithm on industrial data is also presented. Results from the on-line application of the algorithm working in closed loop in the industry are also included. Future work will consist of further industrial testing along with fine-tuning. The final objective is then to have this algorithm integrated in an overall paper machine control system, where other variables, such as basis weight and caliper, are estimated and controlled.

Text

2010-11-17

For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.

http://hdl.handle.net/2429/29989

Electrical and Computer Engineering

University of British Columbia

Graduate