Abstract
White liquor parameters in the recovery area of a kraft pulp mill were monitored for a 1-year period using rhodium as an electrode material in a sensor system based on pulse voltammetry. Shift personnel performed offline titration analysis of the liquor every 4 hours. The results for effective alkali, sulfidity, and total titratable alkali were used to train and validate the sensor for online monitoring. Partial least square regression models developed from 150 reference titration results for each parameter from the first month of the study predicted concentrations for the following 11 months. Validation of the models using titration results indicated that overall relative root mean squared errors for prediction of the parameters were 3.7% for effective alkali, 3.4% for sulfidity, and 5.1% for total titratable alkali. Process stops that exposed the sensor to temperature excursions or acid washings resulted in temporary periods of poor prediction.
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