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On the Statistical process control of Multivariate Autocorrelated processes

IFAC Proceedings Volumes 2000年第10期33卷 165-170页

作者： E. Kaskavelis E.B. Martin A.J. Morris P. Jonathan Centre for Process Analytics and Control Technology Merz Court University of Newcastle NE1 7RU UK Statistical Services Shell Global Solutions Cheshire Innovation Park P.O. Box 1 Chester UK

This paper examines how the dynamic information present in a multivariate set of data can be used to improve the performance of a monitoring scheme of the multivariate mean. Optimum performance of such a scheme requires the use of the covariance/correlation matrix of the time-lagged variables. In the general case, this would require variables to be lagged with respect to one another. A Statistical process control scheme is described where the Mahalanobis distance is monitored based on optimally lagged variables. The benefits of the method are demonstrated using Monte Carlo simulations.

关键词： Multivariate Statistical process control Auto correlation Time Lag

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Monitoring of Multi-Product processes

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IFAC Proceedings Volumes 1999年第2期32卷 6698-6703页

作者： S. Lane E.B. Martin A.J. Morris R.A.G. Kooijmans Centre for Process Analytics and Control Technology University of Newcastle Newcastle upon Tyne NE1 7RU England Unilever Research Vlaardingen PO BOX 114 31310 AC Vlaardingen The Netherlands Fax Number +44 191 222 5748

Traditionally Principal Components Analysis (PCA) has been viewed as a single group method and in particular, in multivariate statistical performance monitoring (MSPM), it has been used as a monitoring and diagnostic tool for single product production. An extension to PCA is presented which enables a number of similar products or product grades to be monitored through a single multi-group model. The method is applied to a semi-discrete industrial batch manufacturing process. The industrial application illustrates that the detection and diagnostic capabilities of the generic model are comparable to those of a single group model.

关键词： Performance Monitoring agile manufacturing chemical industry statistical process control data reduction

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Actuator fault diagnosis in a continuous stirred tank reactor using identification techniques

Actuator fault diagnosis in a continuous stirred tank reacto...

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European control Conference (ECC)

作者： Ron J. Patton C. J. Lopez Toribio Silvio Simani Julian Morris Elaine Martin Jie Zhang School of Engineering University of Hull UK School of Engineering University of Hull Hull Kingston upon Hull GB University of Ferrara Ferrara Italy Centre for Process Analytics and Control Technology (CPACT) University of Newcastle UK

This paper presents a model-based procedure for the detection and isolation of actuator faults in a chemical process. The diagnosis system is based on the estimation of process outputs. A dynamic Multi-input, multiple output (MIMO) process of the process under investigation is obtained by identification procedures, exploiting both Auto Regressive exogenous and Takagi-Sugeno (T-S) fuzzy input-output systems. Fuzzy systems are exploited to cope with different process working conditions. Residual analysis and geometrical tests are then used for fault detection and isolation, respectively. The proposed designs were evaluated using a benchmark simulation of a Continuous Stirred Tank Reactor.

关键词： Mathematical model Actuators Chemical reactors Valves Predictive models Fault detection Inductors

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P1H-2 Particle Sizing in the process Industry using Hertz-Zener Impact Theory and Acoustic Emission Spectra

P1H-2 Particle Sizing in the Process Industry using Hertz-Ze...

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IEEE Symposium (IUS) Ultrasonics

作者： A. Gachagan A. J. Mulholland G. Hayward M. Tramontana A. Nordon G. Carson Department of Mathematics University of Strathclyde Glasgow UK Department of Pure and Applied Chemistry Centre for Process Analytics and Control Technology (CPACT) University of Strathclyde Glasgow UK Department of Electronic and Electrical Engineering The Centre for Ultrasonic Engineering (CUE) University of Strathclyde Glasgow UK

The cost of implementing real-time monitoring and control of industrial processes is a significant barrier for many companies. Acoustic techniques provide complementary information to optical spectroscopic sensors and have a number of advantages: they are relatively inexpensive, can be applied non-invasively, are non-destructive, multi-point measurements are possible, opaque samples can be analysed in containers that are made from opaque materials (e.g. steel or concrete) and the analysis can be conducted in real-time. In this paper a new theoretical model is proposed which describes the transport of particles in a stirred reactor, their collision with the reactor walls, the subsequent vibrations which are then transmitted through the vessel walls, and their detection by an ultrasonic transducer. The particle-wall impact is modelled using Hertz-Zener impact theory. Experimental data is then used in conjunction with this (forward) model to form an inverse problem for the particle size distribution using a least squares cost function. Application of an integral smoothing operator to the power spectra greatly enhances the accuracy and robustness of the approach. One advantage of this new approach is that since it operates in the frequency domain, it can cope with the industrially relevant case of many particle-wall collisions. The technique will be illustrated using data from a set of controlled experiments. In the first instance a set of simplified experiments involving single particles being dropped in air onto a substrate are utilised. The second set of experiments involves particles in a carrier fluid being stirred in a reactor vessel. In each case the approach is able to successfully recover the associated particle size

关键词： Acoustic emission Inductors Optical sensors Information analysis Costs Monitoring process control Industrial control Stimulated emission Spectroscopy

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MULTISCALE FAULT DETECTION AND DIAGNOSIS IN FED-BATCH FERMENTATION

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IFAC Proceedings Volumes 2007年第4期40卷 37-42页

作者： Ahmed Alawi Julian Morris Genzyme Ltd. Hollands Road Haverhill Suffolk CB9 8PU UK Centre for Process Analytics and Control Technology School of Chemical Engineering and Advanced Materials University of Newcastle Newcastle Upon Tyne NE1 7RU UK

The importance of the FDA PAT guidelines in pharmaceutical process design space can be influenced by the introduction of robust process malfunction and senor fault detection and diagnosis tools. The paper compares a multi-scale multi-block modelling approach with conventional multiway PCA approaches for batch process monitoring. A benchmark penicillin fermentation simulation is used to evaluate the two methodologies. Contributions plots with confidence bounds enhance the fault diagnosis potential of the approaches studied. The methodology is in the process of being evaluated in fermentation and batch cooling crystallisation.

关键词： Monitoring Wavelets Multiblock methods Fault detection diagnosis

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SENSOR FAULT DIAGNOSIS IN DYNAMIC processES

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IFAC Proceedings Volumes 2007年第5期40卷 267-272页

作者： Ahmed Alawi Julian Morris Genzyme Ltd. Hollands Road. Haverhill Suffolk. CB9 8PU UK School of Chemical Engineering and Advanced Materials Centre for Process Analytics and Control Technology University of Newcastle Newcastle Upon Tyne NE1 7RU UK

Fault detection and diagnosis are important technologies for the safe and efficient operation of a chemical plant. This paper describes a sensor fault identification approach using variable reconstruction for dynamic systems. The proposed methodology extends sensor fault reconstruction for Canonical Variate Analysis based process performance monitoring which admits process dynamic behaviour in a natural way, and evaluates its capabilities compared to a dynamic PCA approach using a mathematical benchmark problem and a simulation of a closed loop controlled CSTR previously used for studying both simple and complex faults.

关键词： process monitoring Fault diagnosis Fault detection

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Role of Data Mining in Drug Development

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IFAC Proceedings Volumes 2001年第5期34卷 445-450页

作者： E.B. Martin Y. Bissessur A.J. Morris B.V. Kara Centre for Process Analytics and Control Technology University of New castle. Newcastle upon Tyne. NE1 7RU. UK AVECIA Life Science Molecules. Belasis Ave. Billingham. TS23 1 YN. UK AstraZeneca Pharmaceuticals Alderley Park Macclesfield SK 10 4TG UK

Increasing attention is being paid to reducing the time taken from discovery to defining a final fermentation production process. Multivariate statistical data analysis and chemometric techniques can play an important role in contributing to the achievement of this aim by providing biologists and fermentation scientists with sophisticated data visualisation and data exploration tools. This paper presents a study of the application of a range of feature extraction techniques to data from shake flask experiments. investigatingrecombinant protein expression. carried out during the discovery phase of drug development.

关键词： Statistical Analysis Biotechnology Fermentation processes

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Theoretical analysis of chirp excitation of contrast agents

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Physics Procedia 2010年第1期3卷 743-747页

作者： Euan Barlow Anthony J. Mulholland Alison Nordon Anthony Gachagan Department of Mathematics University of Strathclyde 26 Richmond Street Glasgow G1 1XH UK WestCHEM Department of Pure and Applied Chemistry Centre for Process Analytics and Control Technology (CPACT) University of Strathclyde Glasgow G1 1XL UK Department of Electronic and Electrical Engineering The Centre for Ultrasonic Engineering (CUE) University of Strathclyde GlasgowG1 1XW UK

Analytic expressions are found for the amplitude of the first and second harmonics of the Ultrasound Contrast Agent’s (UCA’s) dynamics when excited by a chirp. The dependency of the second harmonic amplitude on the system parameters, the UCA shell parameters, and the insonifying signal parameters is then investigated. It is shown that optimal parameter values exist which give rise to a clear increase in the second harmonic component of the UCA’s motion.

关键词： Ultrasound contrast agent Chirp Second harmonic Theoretical Small parameter perturbation

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Pocket-size near-IR spectrometers for rapid examination of contaminated textile fibres at the crime-scene

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Vibrational Spectroscopy 2022年 123卷

作者： Rashed, Hamad S. Parrott, Andrew J. Nordon, Alison Baker, Matthew J. Palmer, David S. Department of Pure and Applied Chemistry University of Strathclyde Technology and Innovation Centre 99 George Street GlasgowG1 1RD United Kingdom Trace Evidence Section General Department of Forensic Science and Criminology Dubai Police GHQ Dubai United Arab Emirates Department of Pure and Applied Chemistry and Centre for Process Analytics and Control Technology University of Strathclyde Royal College Building 204 George Street GlasgowG1 1XW United Kingdom Department of Pure and Applied Chemistry University of Strathclyde Thomas Graham Building 295 Cathedral Street GlasgowG1 1XL United Kingdom School of Medicine Faculty of Clinical and Biomedical Sciences University of Central Lancashire Fylde Rd PrestonPR1 2HE

In a typical forensic investigation, fabric analysis plays a vital role in solving different crimes. Several types of textile fibre materials (cotton, polyester, denim, polypropylene, polycotton, and viscose) were analysed in the presence of common contaminants (blood, rainwater, seawater, sand and gunshot-residue) to evaluate the performance of two NIR spectrometers for in situ analysis of different crime scene conditions. The spectrometers used were SCIO® by Consumer Physics and NIRscan Nano by Texas Instruments. The SCIO instrument covers the third overtone region (740–1070 nm) and NIRscan Nano instrument covers the first and second overtone regions (900–1700 nm). Spectra from both instruments were pre-processed using the PRFFECTv2 software to eliminate noise and smooth the data for classification model construction. The models showed high accuracy, sensitivity and specificity with a range of 69–100% for binary classification (one class versus others) and range of 76–100% for multi-class classification of fibre material. This study shows for the first time the capability of pocket-size spectrometers coupled with random forest models for classification of fibre material in the presence of common contaminants in a rapid and non-destructive manner, and so is suitable for investigation of crime scenes. © 2022 The Authors

关键词： Spectrometers

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