Nayak, JK and Prasad, V and Ganguli, R (2021) A field programmable gate array (Fpga) based non-linear filters for gas turbine prognostics. In: International Journal of Prognostics and Health Management, 12 (3). pp. 1-12.
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Abstract
The removal of noise from signals obtained through the health monitoring systems in gas turbines is an important consideration for accurate prognostics. Several filters have been designed and tested for this purpose, and their performance analysis has been conducted. Linear filters are inefficient in the removal of outliers and noise because they cause smoothening of the sharp features in the signal which can indicate the onset of a fault event. On the other hand, non-linear filters based on image processing methods can provide more precise results for gas turbine health signals. Among others, the weighted recursive median (WRM) filter has been shown to provide greater accuracy due to its weight adaptability depending on the signal type. However, sampling data at high rates is possible which needs hardware implementation of the filter. In this paper, the design, simulation and implementation of WRM filters on the FPGA (Field Programmable Gate Arrays) platforms Vivado Design Suite by Xilinx and Quartus Pro Lite Edition 19.3 has been performed. The architectural detail and performance result with the FPGA filters when subjected to abrupt and gradual fault signal is presented. © 2021, Prognostics and Health Management Society. All rights reserved.
| Item Type: | Journal Article |
|---|---|
| Publication: | International Journal of Prognostics and Health Management |
| Publisher: | Prognostics and Health Management Society |
| Additional Information: | The copyright for this article belongs to Authors |
| Department/Centre: | Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering) |
| Date Deposited: | 18 Aug 2021 10:50 |
| Last Modified: | 18 Aug 2021 10:50 |
| URI: | http://eprints.iisc.ac.in/id/eprint/69274 |
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