Improved fault diagnosis in multivariate systems using regression-based reconstruction

Subspace monitoring has recently been proposed as a condition monitoring tool that requires considerably fewer variables to be analysed compared to dynamic principal component analysis (PCA). This paper analyses subspace monitoring in identifying and isolating fault conditions, which reveals that the existing work suffers from inherent limitations if complex fault senarios arise. Based on the assumption that the fault signature is deterministic while the monitored variables are stochastic, the paper introduces a regression-based reconstruction technique to overcome these limitations. The utility of the proposed fault identification and isolation method is shown using a simulation example and the analysis of experimental data from an industrial reactive distillation unit.

Prognostic significance of combined MN1, ERG, BAALC, and EVI1 (MEBE) expression in patients with myelodysplastic syndromes

Overexpression of MN1, ERG, BAALC, and EVI1 (MEBE) genes in cytogenetically normal acute myeloid leukemia (AML) patients is associated with poor prognosis, but their prognostic effect in patients with myelodysplastic syndromes (MDS) has not been studied systematically. Expression data of the four genes from 140 MDS patients were combined in an additive score, which was validated in an independent patient cohort of 110 MDS patients. A high MEBE score, defined as high expression of at least two of the four genes, predicted a significantly shorter overall survival (OS) (HR 2.29, 95 % CI 1.3-4.09, P?=?.005) and time to AML progression (HR 4.83, 95 % CI 2.01-11.57, P?