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在受传感器退化和故障影响的系统控制中的风险评估框架
Tangxiao Yuan1,2, Weilin Xu1, Kondo Hloindo Adjallah2
1School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
Sensors (Basel, Switzerland)
|March 13, 2024
概括
传感器故障可能会削弱对数据驱动决策的信任. 本研究引入了风险评估框架,以评估和预测由传感器退化引起的决策错误,提高系统可靠性.
科学领域:
- 计算机科学 计算机科学
- 工程 工程师 工程师 工程师
- 风险管理 风险管理
背景情况:
- 传感器退化和故障对数据驱动决策模型的可靠性构成重大挑战.
- 对于采用新的决策系统的信心,特别是在风险敏感的应用中,通常会因为传感器的不可靠性而受到损害.
研究的目的:
- 引入一个专门为分类算法设计的新风险评估框架.
- 评估和量化来自传感器退化和故障的决策风险.
主要方法:
- 该框架涉及现场无故障和故障数据收集,故障数据生成和模拟决策过程.
- 它包括风险识别,定量风险评估和风险预测的步骤.
- 该方法通过在访问控制系统中的案例研究来验证.
主要成果:
- 该框架允许用户根据当前数据收集状态评估潜在的决策错误.
- 它可以对传感器数据的风险敏感度进行排名,以便在采用模型之前优化数据收集.
- 该方法通过考虑传感器寿命,为维护策略提供信息来促进预测未来的系统风险.
结论:
- 开发的风险评估框架通过解决传感器可靠性问题,提高了对数据驱动决策的信心.
- 它提供了一种系统的方法来识别,量化和预测与传感器退化相关的风险.
- 这些发现支持主动的传感器维护和优化数据收集,以提高系统性能和安全性.
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