A model based approach for determining data quality metrics in combustion pressure measurement. A study into a quantative based improvement in data quality
SupervisorEbrahimi, Kambiz M.
Mason, Byron A.
MetadataView full catalogue record
KeywordsCombustion measurement; Internal combustion engine; Data quality; Result calculation; Simulation; Modelling; Error simulation; Combustion pressure; Internal combustion
The University of Bradford theses are licenced under a Creative Commons Licence.
InstitutionUniversity of Bradford
DepartmentFaculty of Engineering and Informatics
This thesis details a process for the development of reliable metrics that could be used to assess the quality of combustion pressure measurement data - important data used in the development of internal combustion engines. The approach that was employed in this study was a model based technique, in conjunction with a simulation environment - producing data based models from a number of strategically defined measurement points. A simulation environment was used to generate error data sets, from which models of calculated result responses were built. This data was then analysed to determine the results with the best response to error stimulation. The methodology developed allows a rapid prototyping phase where newly developed result calculations may be simulated, tested and evaluated quickly and efficiently. Adopting these newly developed processes and procedures, allowed an effective evaluation of several groups of result classifications, with respect to the major sources of error encountered in typical combustion measurement procedures. In summary, the output gained from this work was that certain result groups could be stated as having an unreliable response to error simulation and could therefore be discounted quickly. These results were clearly identifiable from the data and hence, for the given errors, alternative methods to identify the error sources are proposed within this thesis. However, other results had a predictable response to certain error stimuli, hence; it was feasible to state the possibility of using these results in data quality assessment, or at least establishing any boundaries surrounding their application for this usage. Interactions in responses were also clearly visible using the model based sensitivity analysis as proposed. The output of this work provides a solid foundation of information from which further work and investigation would be feasible, in order to achieve an ultimate goal of a full set of metrics from which combustion data quality could be accurately and objectively assessed.
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