KNOWLEDGE EXTRACTION FROM THE EDDY CURRENT MEASUREMENT DATA
Pawel Frankowski
pawel.frankowski@sk.sep.szczecin.plWest Pomeranian University of Technology in Szczecin (Poland)
Abstract
The purpose of this paper is to present methods, dedicated for extract useful patterns from the eddy current measurement data. The paper presents a methodology of knowledge extraction, an association rule learning algorithm and the methods used to improve quality of the data collected by electromagnetic systems. Presented solutions were implemented in the new eddy current system used to evaluation of steel bars in reinforced concrete structures.
Keywords:
data analysis, association rules, eddy currents, reinforcement concrete structuresReferences
Agrawal R, Srikant R.: Fast algorithms for mining association rules in large databases, Proceedings of the 20th International Conference on Very Large Data Bases, 1994, s. 487-499.
Google Scholar
Chady T., Frankowski P.: Electromagnetic Evaluation of Reinforced Concrete Structure, Review Of Progress in Quantitative Nondestructive Evaluation, Vol.32, 2013, s. 1355-1362.
Google Scholar
Drobiec Ł., Jasiński R., Piekarczyk A.: Diagnostyka konstrukcji żelbetowych – Tom 1. PWN, Warszawa 2010.
Google Scholar
Shearer C.: The CRISP-DM model: the new blueprint for data mining, J Data Warehousing, nr 5/2000, s. 13-22.
Google Scholar
Zybura A., Jaśniok A., Jaśniok T.: Diagnostyka konstrukcji żelbetowych, Tom 2. PWN, Warszawa 2011.
Google Scholar
Authors
Pawel Frankowskipawel.frankowski@sk.sep.szczecin.pl
West Pomeranian University of Technology in Szczecin Poland
Statistics
Abstract views: 214PDF downloads: 64
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
