Fault reconstruction in linear dynamic systems using multivariate statistics

Treasure et al. (2004) recently proposed a new sub space-monitoring technique, based on the N4SID algorithm, within the multivariate statistical process control framework. This dynamic-monitoring method requires considerably fewer variables to be analysed when compared with dynamic principal component analysis (PCA). The contribution charts and variable reconstruction, traditionally employed for static PCA, are analysed in a dynamic context. The contribution charts and variable reconstruction may be affected by the ratio of the number of retained components to the total number of analysed variables. Particular problems arise if this ratio is large and a new reconstruction chart is introduced to overcome these. The utility of such a dynamic contribution chart and variable reconstruction is shown in a simulation and by application to industrial data from a distillation unit.

Improved reliability in diagnosing faults using multivariate statistics

This paper analyses multivariate statistical techniques for identifying and isolating abnormal process behaviour. These techniques include contribution charts and variable reconstructions that relate to the application of principal component analysis (PCA). The analysis reveals firstly that contribution charts produce variable contributions which are linearly dependent and may lead to an incorrect diagnosis, if the number of principal components retained is close to the number of recorded process variables. The analysis secondly yields that variable reconstruction affects the geometry of the PCA decomposition. The paper further introduces an improved variable reconstruction method for identifying multiple sensor and process faults and for isolating their influence upon the recorded process variables. It is shown that this can accommodate the effect of reconstruction, i.e. changes in the covariance matrix of the sensor readings and correctly re-defining the PCA-based monitoring statistics and their confidence limits. (c) 2006 Elsevier Ltd. All rights reserved.

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.

Absolute Calibration of Atomic Density Measurements by Laser-Induced Fluorescence Spectroscopy with Two-Photon Excitation (TALIF)

The two-photon resonances of atomic hydrogen (? = 2 × 205.1 nm), atomic nitrogen (? = 2 × 206.6 nm) and atomic oxygen (? = 2 × 225.6 nm) are investigated together with two selected transitions in krypton (? = 2×204.2 nm) and xenon (? = 2×225.5 nm). The natural lifetimes of the excited states, quenching coefficients for the most important collisions partners, and the relevant ratios of the two-photon excitation cross sections are measured. These data can be applied to provide a calibration for two-photon laser-induced fluorescence measurements based on comparisons with spectrally neighbouring noble gas resonances.

Measurement of Quenching Coefficients and Developement of Calibration Methods for Quantitative Spectroscopy of Plasma at Elevated Pressures

Measurements of collisional de-excitation (quenching) coefficients required for the interpretation of emission and fluorescence spectroscopic measurements are reported. Particular attention is turned on argon transitions which are of interest for actinometric determinations of atomic ground state populations and on fluorescence lines originating from excited atoms and noble gases in connection with two-photon excitation (TALIF) of atomic radicals. A novel method is described which allows to infer quenching coefficients for collisions with molecular hydrogen of noble gas states in the energy range up to 24 eV. The excitation is performed in these experiments by collisions of energetic electrons in the sheath of an RF excited hydrogen plasma during the field reversal phase which lasts about 10 ns. We describe in addition a calibration method - including quenching effects - for the determination by TALIF of absolute atomic radical densities of hydrogen, nitrogen and oxygen using two-photon resonances in noble gases close by the resonances of the species mentioned. The paper closes with first ideas on a novel technique to bypass quenching effects in TALIF by introducing an additional, controllable loss by photoionization that will allow quenching-free determination of absolute atomic densities with prevalent nanosecond laser systems in situations where collisional de-excitation dominates over spontaneous emission.

Multivariate Statistical Analysis Applied to an IL6 Signal Transduction Model in Hepatocytes

This paper introduces the application of linear multivariate statistical techniques, including partial least squares (PLS), canonical correlation analysis (CCA) and reduced rank regression (RRR), into the area of Systems Biology. This new approach aims to extract the important proteins embedded in complex signal transduction pathway models.The analysis is performed on a model of intracellular signalling along the janus-associated kinases/signal transducers and transcription factors (JAK/STAT) and mitogen activated protein kinases (MAPK) signal transduction pathways in interleukin-6 (IL6) stimulated hepatocytes, which produce signal transducer and activator of transcription factor 3 (STAT3).A region of redundancy within the MAPK pathway that does not affect the STAT3 transcription was identified using CCA. This is the core finding of this analysis and cannot be obtained by inspecting the model by eye. In addition, RRR was found to isolate terms that do not significantly contribute to changes in protein concentrations, while the application of PLS does not provide such a detailed picture by virtue of its construction.This analysis has a similar objective to conventional model reduction techniques with the advantage of maintaining the meaning of the states prior to and after the reduction process. A significant model reduction is performed, with a marginal loss in accuracy, offering a more concise model while maintaining the main influencing factors on the STAT3 transcription.The findings offer a deeper understanding of the reaction terms involved, confirm the relevance of several proteins to the production of Acute Phase Proteins and complement existing findings regarding cross-talk between the two signalling pathways.