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Results for "supervisors_tesim:"Huang, Biao (Chemical and Materials Engineering)""
Time consuming offline laboratory analysis and high cost hardware measurement techniques render difficulties in obtaining the important quality variables in real time application. Near-infrared (NIR) spectroscopy is widely used as a process analytical tool (PAT) in chemical processes, providing...
In this thesis, time-varying behaviour, nonlinearity and switching dynamics are generally treated as multi-modal behaviour. Two multi-model modelling techniques, i.e., the linear parameter varying (LPV) technique and the switched modelling technique, are investigated to model the multi-modal...
Management of abnormal events in chemical processes requires detection and diagnosis of abnormal performance of individual elements of the system. Detection of abnormal performance is usually done by means of setting a control limit on measured variables. Abnormality due to any reason in one...
Data Quality Assessment for Closed-Loop System Identification and Forecasting with Application to Soft SensorsDownload
In many chemical plants, data historians store thousands of variables at fast sampling rates. Much of this collected data is routine operating data that could easily be used for system identification and forecasting, especially in the design of soft sensors. Currently, there is no framework for...
Limitations of measurement techniques and increasingly complex chemical process render difficulties in obtaining certain critical process variables. The hardware sensor reading may have an obvious bias compared with the real value. Off-line laboratory analysis with high accuracy can only be...
Availability of large amounts of industrial process data is allowing researchers to explore new data-based modelling methods. In this thesis, Gaussian process (GP) regression, a relatively new Bayesian approach to non-parametric data based modelling is investigated in detail. One of the primary...
In many industrial processes, critical variables cannot be easily measured on-line: they are either obtained from hardware analyzers which are often expensive and difficult to maintain, or carried out off-line through laboratory analysis which cannot be used in real time control. These...
A number of industrial processes involve variables that cannot be reliably measured in real time using online sensors. Many such variables are required as inputs in control schemes to ensure safe and efficient plant operation. Laboratory analysis, which is a reliable method of measuring these...
Pattern Recognition of Time-dependent Cellular Response of Chemicals Based on Profile Shape SimilarityDownload
As a potential approach to interpret Mode of Action (MoA), the shape of cellular response profiles associated with chemicals has been a key consideration. In this thesis, statistical pattern recognition methods using multiconcentration time-dependent cellular response profiles (TCRPs) are...
A large volume of literature exists on fault detection and isolation for industrial processes. In a general view, these various methods may be divided into process model based and process history based fault diagnosis. In both classes, there has been a recent focus on extracting the temporal...