Live Demonstration: AI-based System Latchup Detection and Protection for COTS Systems
The adoption of Commercial Off-The-Shelf (COTS) ICs in modern satellites faces challenges from radiation-induced latchup events, with current protection methods showing significant limitations in detection accuracy and applicability. This demonstration presents a novel adaptive AI-based latchup detection and protection system featuring two-stage training and LSTM neural network analysis. Our FPGA implementation achieves 90% detection accuracy without extensive pre-characterization. Visitors can validate the system's performance through real-time interaction with various latchup scenarios.
Authors
- Joseph S. Chang (ORCID: https://orcid.org/0000-0003-0991-8339)
- Wei Shu (ORCID: https://orcid.org/0000-0003-0890-2634)
- Tony Zhang (ORCID: https://orcid.org/0009-0009-0288-8270)
- Kwen‐Siong Chong (ORCID: https://orcid.org/0000-0003-1512-2003)
- Rouli Fang (ORCID: https://orcid.org/0000-0003-3800-0180)
- Junkai Zhao (ORCID: https://orcid.org/0000-0001-9901-4338)
- Yin Sun (ORCID: https://orcid.org/0000-0002-1121-9492)
Institutions
- Nanyang Technological University (SG)
Publication Details
- Published
- 2025-05-25
- DOI
- https://doi.org/10.1109/iscas56072.2025.11044028
- Primary Topic
- Software System Performance and Reliability
- Type
- article
- Field-Weighted Citation Impact
- 0.00