کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5132349 | 1491520 | 2016 | 11 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Transfer of a static PCA-MSPC model from a steady-state anaerobic reactor to an independent anaerobic reactor exposed to organic overload Transfer of a static PCA-MSPC model from a steady-state anaerobic reactor to an independent anaerobic reactor exposed to organic overload](/preview/png/5132349.png)
- An anaerobic reactor was overfed until VFA intoxication and compared to a steady-state reactor.
- A static PCA-MSPC model was successfully transferred between the two reactors.
- The TA² and SPE control chart provided early warning of the AD process dysfunctions.
- The gas composition (CH4, CO2, H2) was the major contributor of this warning.
A static multivariate statistical process control model based on principal component analysis (PCA-MSPC) was developed for an anaerobic reactor maintained in steady-state, joining the biogas composition (CH4, CO2, H2) to the total solids (TS), volatile solids (VS), total inorganic carbon (TIC) and total ammonia nitrogen (TAN) contents of the slurry. The principal component analysis (PCA) highlighted a lack of correlation between the individual process variables (IPVs) measured in the slurry and the gas phase. The application of this model to the data set collected for an independent anaerobic reactor (fed with the same substrate) progressively led from steady-state to critical volatile fatty acids (VFA) intoxication did not allow evaluating its process status. A second static PCA-MSPC model was built for the steady-state reactor in excluding the TS and VS content of the slurry and was successfully transferred to the overfed reactor. The TA² and SPE control charts built for the overfed reactor using this second model closely reflected its process status and delivered valuable warning signals approaching the VFA intoxication. The gas phase composition (CH4, CO2, H2) brought the main contribution to these warnings.
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 159, 15 December 2016, Pages 20-30