计算机科学
断层(地质)
容错
遗传算法
陷入故障
补偿(心理学)
故障覆盖率
实时计算
算法
嵌入式系统
故障检测与隔离
分布式计算
电子线路
工程类
人工智能
地质学
精神分析
电气工程
地震学
心理学
机器学习
执行机构
作者
Jie Wang,Junjie Kang,Gang Hou
出处
期刊:IEEE Access
[Institute of Electrical and Electronics Engineers]
日期:2019-01-01
卷期号:7: 35805-35815
被引量:16
标识
DOI:10.1109/access.2019.2905042
摘要
Fault-tolerant systems are indispensable for complex electronic systems, but there are some drawbacks to the traditional fault-tolerant schemes. The evolution of hardware for fault-tolerant systems can achieve good results. However, because of the highly time-consuming evolution process, the evolution approach may not meet the real-time constraint for fault recovery. In this paper, we propose an improved genetic algorithm for real-time circuit fault recovery. We establish a real-time fault-tolerant system on a ZYNQ chip. In this system, a fault analysis tree hierarchically monitors a circuit fault. When the fault occurs, the normal operation of the faulty circuit is temporarily maintained by a fault compensation mechanism. At the same time, we use an evolutionary mechanism combined with a fault recovery library and improved genetic algorithm to accelerate the evolution of the repair circuit and obtain a repaired circuit while the fault compensation mechanism is running. Ultimately, the improved algorithm significantly improves the fault-tolerant recovery rate and ensures the operations in real time. Thus, the improved genetic algorithm for real-time circuit fault recovery can meet the system's real-time constraints and improve the system's stability.
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