Abstract
The operation of continuous pulp digesters play a pivotal role in the profitability of a pulp mill. Particularly, process faults due to the non-ideal flow behaviour in the digester have direct impact on the pulp quality, production rate and chemical utilization of the plant. The study begins with an introduction on process faults in continuous reactors by explicitly focusing on continuous pulp digesters. Operational data from a commercial pulp digester is analysed to examine process abnormalities. Subsequently, the extended Purdue model is modified to simulate non-ideal flows related continuous digester faults. The affect of different process faults on important process variables are analysed with the help of simulation studies. In the second part of the paper, a hybrid fault diagnostics approach based on first-principle digester model and Bayesian network is proposed and validated. Additionally, the methodology of developing the diagnostics approach are also described.
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