Optical Sensing Based Technology Applied To Pulp And Paper Related Measurements

Pulp and paper industry is one of the traditional processes that have the problems associated with high energy-consumption and high pollution. For the substantable development, it is important to make the effort on the energy saving and pollution reduction in pulp and paper industry. If the parameters of processes or finished products were quickly determined, the timely adjustment on the process parameters and conditions can be performed, from which it ont only saves the raw materials, chemical agents and energy, but also reduces the pollution discharded to environment. Moreover, it can effectively prevent the equipment failure from production system and objectively evaluate the quality or performance of the products, aiming at the cost-effectiveness in pulp and paper manufacturing. Therefore, it is important to apply the advanced automatic detection technology into the pulp and paper. The measurement technology based on the optical sensing is usally non-destructive, rapid and sensitive, and thus it is suitable for the analysis of all kinds of liquids and solid materials. In this thesis, the studies were done on the following subjects:Since the control of cooking process was very important and the precision of the existing control model of continuous and displacement cooking can not meet the requirements of industrial manufacturing process, the kappa number on-line monitoring model for the cooking process was established based on the ATR-UV optical sensor. According to some researches, the relationship between the Kappa number and the residual lignin content in the pulp is linear. Because the wood and the lignin in the wood follow the law of conservation of mass through all the cooking time, the residual lignin in the pulp can be get according the dissolved lignin in the cooking liquor. While the concentration of the dissolved lignin in the cooking liquor could be tested by the ATR-UV optical sensor, then was integrated with the fluid flowrate for the cooking time to obtain the dissolved lignin in real time. The control models of continuous and displacement cooking process were established on the basis of the kappa number on-line monitoring model, respectively.Since the detection technology of the pulp brightness was defective in China and the brightness sensors of pulp from foreign countries were too expensive, the brightness meter of the pulp was developed, which was quick and smart. The determination model of the pulp brightness was built based on the slurry that is universal and suitable for all types of slurry. The pulp brightness intelligent meter was developed on the basis of the detection model. The measurement principle was diffuse blue reflectance factor. The operation control platform was written by Lab VIEW and it can detect the samples automatically. Moreover, it can process the testing data intelligently. This had laid a solid foundation for online brightness sensor of pulp research and development.Since the Kappa number is very important to be detected rapidly and the existing testing instruments still leave much to be desired, the Kappa number analyzer was developed based on visible transmittance spectral analysis technique. The upper computer system software was written by Lab VIEW, and the lower computer system software was written by C-51 language. The single chip microcomputer(STC 51) was used. At last, the full-automated detection was obtained on the analyzer.To promote the waste paper recycling, and to ensure the quality and safety of the tissue paper and food wrapping paper, an efficient, convenient and reliable method that is used for discriminating the recycled fiber in the products was established. The method of identification of tissue paper made from blended recycled fiber was built based on the traditional characteristic detection and pattern recognition technology. It had a better recognition rate than the traditional methods, but still was complicated and time-consuming because the characteristics of paper need to be examined. So another method was built based on near infrared optical sensors and pattern recognition technology to identify whether the tissue paper blended with recycled fiber, that was accurate, convenient and no sample processing, and the recognition rate was 100%. This laid a solid foundation for the development of special sensor to identify recycled fiber in tissue paper. On the basis of above research, the quantitative analysis method of recycled fiber content in the paper was established based on near infrared optical sensor technology combined with multivariate regression analysis.