A Hierarchical Statistical Process Monitoring Strategy for Multivariable Multi-rate Industrial Processes
Computer Science and Information Engineering, World Congress on (2009)
Los Angeles, California USA
Mar. 31, 2009 to Apr. 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.259
A hierarchical statistical process monitoring strategy is proposed for the industrial processes with multivariable multi-rate sampled measurements. By making full use of multi-rate measurements, two-level models are adopted where the sub-PCA models are built on high-rate measurements to ensure timely abnormality detection and the super Multi-block PCA model is built on the lifted process measurements to monitor the overall operating performance. The ability of the proposed strategy is demonstrated with the benchmark TE process.
L. Jianhua and L. Ningyun, "A Hierarchical Statistical Process Monitoring Strategy for Multivariable Multi-rate Industrial Processes," 2009 WRI World Congress on Computer Science and Information Engineering, CSIE(CSIE), Los Angeles, CA, 2009, pp. 262-266.