Details of Grant 

EPSRC Reference:	GR/M67728/01
Title:	TOOLKITS FOR ADVANCED SENSOR VALIDATION CONDITION MONITORING & MODELLING OF WATER TREATMENT SYSTEMS
Principal Investigator:	Cox, Professor C
Other Investigators:	Montague, Professor G Willis, Dr M Fletcher, Dr I Tham, Dr M Fletcher, Dr I Willis, Dr M
Researcher Co-Investigators:
Project Partners:	AKZO Nobel Foundation for Water Research North West Water Northumbrian Water Ltd Prism Ltd Thames Water Plc Yorkshire Water
Department:	Computing Engineering and Technology
Organisation:	University of Sunderland
Scheme:	Standard Research (Pre-FEC)
Starts:	01 September 1999	Ends:	31 August 2002	Value (£):	241,406
EPSRC Research Topic Classifications:	Water Engineering
EPSRC Industrial Sector Classifications:	Water
Related Grants:
Panel History:
Summary on Grant Application Form
This proposal aims to develop software methodologies that should enable discrimination between sensor and plant faults; provide signal reconstruction when it is required and offer improved process diagnosis. By using distributed intelligence and an integrated structured communications protocol, it is hoped that past problems relating to fragmented uncoordinated decision support would be avoided. The work is targeted specifically for exploitation at water treatment works.The philosophy is to build on existing smart sensor technologies by developing toolkits based upon multivariate statistical process control, artificial neural networks and fractal analysis. These new techniques offer the advantage that multivariate data can be fused to provide 'improved performance indicating information' and consequently, enhance the efficiency of the final control policies. The intention is to also take advantage, where possible, of strategies under development in the gas, nuclear, aerospace and petrochemical industries.The proposal has attracted a unique set of collaborators, who pledge their expertise and experience to develop and validate the various software modules under a wide range of different process conditions. Industrial partners are also prepared to make available plant for experimentation and on-line algorithm testing. These should provide critical evidence of the potential and portability of the new solutions.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Further Information:
Organisation Website:	http://www.sund.ac.uk