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Title: Numerical modelling and in-process expert system for the assessment of large scale seals
Author: Abubake Jimoh, Ismail
ISNI:       0000 0004 5372 0626
Awarding Body: University of Bolton
Current Institution: University of Bolton
Date of Award: 2015
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The design and development of large scale seals, under a variety of loads and how they can be monitored for fault diagnosis and life prediction, have been investigated in this study. The work builds upon ideas of developing a physically based mathematical model of an elastomeric lip seal. The approach utilised finite element analysis to simulate its in-service operating condition, in order to obtain parameters needed to be considered for credible life performance of such seal, and therefore allow an extension for new large scale problems, in which the application can be used under increased loads. Accurate modelling requires the knowledge of the boundary condition, material properties and some real life data, which are key parameters to developing a reliable optimised model and a system to enable condition monitoring of seal. The material properties of an elastomer, subjected to tension and compression loads are obtained in this work, whilst putting into consideration the large strain nonlinear elasticity exhibited by the materials. Hyperelastic material models were utilised, since they put into consideration material nonlinearity of elastomers. This eliminates the shortcomings of the conventional Hookean material law currently used in the industries for seal design study. Considering the potential for the demand of a seal monitoring and diagnostic system in the future, this thesis introduces a new, in-process cognitive expert system structure. The structure consists of a knowledge base and an inference model, that is able to evaluate the fault severity of a seal system based on the knowledge provided to it. A case study herein reveals that the structure is able to retain control rules taught to it for the assessment of a sealing process. A computer simulation has been used to analyse, illustrate and evaluate the reliability of the structure, and it shows that it can play a key role in successful application of artificial intelligence technique to monitor the seal and similar assets.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available