التفاصيل البيبلوغرافية
| العنوان: |
A Field Programmable Gate Array (FPGA) Based Non-Linear Filters for Gas Turbine Prognostics |
| المؤلفون: |
Jayant Kumar Nayak, Vatsala Prasad, Ranjan Ganguli |
| المصدر: |
International Journal of Prognostics and Health Management, Vol 12, Iss 3 (2021) |
| بيانات النشر: |
The Prognostics and Health Management Society, 2021. |
| سنة النشر: |
2021 |
| المجموعة: |
LCC:Systems engineering |
| مصطلحات موضوعية: |
field programmable gate array, gas turbine, prognostics, Engineering machinery, tools, and implements, TA213-215, Systems engineering, TA168 |
| الوصف: |
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. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
2153-2648 |
| Relation: |
https://papers.phmsociety.org/index.php/ijphm/article/view/2960; https://doaj.org/toc/2153-2648 |
| DOI: |
10.36001/ijphm.2021.v12i3.2960 |
| URL الوصول: |
https://doaj.org/article/42ecdbc029374c3dbc070e04ede08bb0 |
| رقم الانضمام: |
edsdoj.42ecdbc029374c3dbc070e04ede08bb0 |
| قاعدة البيانات: |
Directory of Open Access Journals |