- Home
- Search Results
- Page 1 of 1
Search for: All records
-
Total Resources3
- Resource Type
-
0001000002000000
- More
- Availability
-
03
- Author / Contributor
- Filter by Author / Creator
-
-
Li, Gang (3)
-
Mayfield, William (3)
-
Qin, Zhichang (1)
-
Zhu, Weidong (1)
-
#Tyler Phillips, Kenneth E. (0)
-
#Willis, Ciara (0)
-
& Abreu-Ramos, E. D. (0)
-
& Abramson, C. I. (0)
-
& Abreu-Ramos, E. D. (0)
-
& Adams, S.G. (0)
-
& Ahmed, K. (0)
-
& Ahmed, Khadija. (0)
-
& Aina, D.K. Jr. (0)
-
& Akcil-Okan, O. (0)
-
& Akuom, D. (0)
-
& Aleven, V. (0)
-
& Andrews-Larson, C. (0)
-
& Archibald, J. (0)
-
& Arnett, N. (0)
-
& Arya, G. (0)
-
- Filter by Editor
-
-
& Spizer, S. M. (0)
-
& . Spizer, S. (0)
-
& Ahn, J. (0)
-
& Bateiha, S. (0)
-
& Bosch, N. (0)
-
& Brennan K. (0)
-
& Brennan, K. (0)
-
& Chen, B. (0)
-
& Chen, Bodong (0)
-
& Drown, S. (0)
-
& Ferretti, F. (0)
-
& Higgins, A. (0)
-
& J. Peters (0)
-
& Kali, Y. (0)
-
& Ruiz-Arias, P.M. (0)
-
& S. Spitzer (0)
-
& Sahin. I. (0)
-
& Spitzer, S. (0)
-
& Spitzer, S.M. (0)
-
(submitted - in Review for IEEE ICASSP-2024) (0)
-
-
Have feedback or suggestions for a way to improve these results?
!
Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher.
Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?
Some links on this page may take you to non-federal websites. Their policies may differ from this site.
-
This paper presents a trusted execution environment (TEE)-enhanced federated learning (FL) framework for condition monitoring of distributed wind systems (DWSs). DWSs have become a topic of interest with the increased energy demand. Technological advancements in wind turbine technology have paved the way for DWSs to make a massive impact on the power grid. Due to underdeveloped security, malicious groups and individuals can target individual turbines, gain control of wind farms, and ultimately threaten the overall power grid. TEE-enhanced FL offers a solution; however, there are some challenges to its implementation. The remainder of this paper will discuss the challenges further and present solutions to their respective challenges. These solutions have been validated through experimentation and confirm an effective FL framework balancing both practicality and security in DWSs.more » « lessFree, publicly-accessible full text available November 26, 2026
-
Mayfield, William; Li, Gang (, American Society of Mechanical Engineers)Abstract This paper presents a trusted execution environment (TEE)-enhanced federated learning (FL) framework for condition monitoring of distributed wind systems (DWSs). DWSs have become a topic of interest with the increased energy demand. Technological advancements in wind turbine technology has paved the way for DWSs to make a massive impact on the power grid. Due to underdeveloped security, malicious groups and individuals can target individual turbines, gain control of wind farms, and ultimately threaten the overall power grid. TEE-enhanced FL offers a solution, however, there are some challenges to their implementation. The remainder of this paper will discuss the challenges further and present solutions to their respective challenges. These solutions have been validated through experimentation and confirm an effective FL framework balancing both practicality and security in DWSs.more » « lessFree, publicly-accessible full text available July 8, 2026
-
Qin, Zhichang; Li, Gang; Zhu, Weidong; Mayfield, William (, Ocean Engineering)Free, publicly-accessible full text available June 1, 2026
An official website of the United States government
