Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6955458 | Mechanical Systems and Signal Processing | 2016 | 12 Pages |
Abstract
This paper presents a new and improved fully automatic delta T mapping technique where a clustering algorithm is used to automatically identify and select the highly correlated events at each grid point whilst the “Minimum Difference” approach is used to determine the source location. This removes the requirement for operator expertise, saving time and preventing human errors. A thorough assessment is conducted to evaluate the performance and the robustness of the new technique. In the initial test, the results showed excellent reduction in running time as well as improved accuracy of locating AE sources, as a result of the automatic selection of the training data. Furthermore, because the process is performed automatically, this is now a very simple and reliable technique due to the prevention of the potential source of error related to manual manipulation.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Safaa Kh. Al-Jumaili, Matthew R. Pearson, Karen M. Holford, Mark J. Eaton, Rhys Pullin,