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Data Mining and Optimization Tools for Developing Engine Parameters ToolsThis project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.
Document ID
20000021063
Document Type
Contractor or Grantee Report
Authors
Dhawan, Atam P. (Toledo Univ. OH United States)
Date Acquired
August 19, 2013
Publication Date
December 21, 1998
Subject Category
Aircraft Propulsion and Power
Funding Number(s)
CONTRACT_GRANT: NAG3-2181
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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