Comparative Study of Health Monitoring Sensors based on Prognostic Performance

H. Park, N. Kim, Jooho Choi
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引用次数: 1

Abstract

In the safety critical systems such as industrial plants or aircraft, failure occurs inevitably during the operation, and it is important to prevent this while maintaining high availability. Therefore, a lot of efforts are being directed toward developing advanced prognostics algorithms and sensing techniques as an enabler for predictive maintenance. The key for reliable and accurate prediction not only relies on the prognostics algorithms but also based on the collection of sensor data. However, there is not much in-dept studies toward evaluating the varying sensing techniques based on the prediction performance and inspection scheduling. It would be more reasonable for practitioner to select different cost of sensors based on the sensors’ contribution on reducing the cost on unnecessary inspection or measurement while maintaining its prognosis performance. Thus, the authors try to thoroughly evaluate the cost-effectiveness of the different sensor with respect to sensor resistance to noise. The simulation is conducted to analyze the prediction performance with varying measurement interval and different level of noise during degradation. Then real run-to-fail (RTF) dataset acquired from two different sensors are analyzed to design optimal measurement system for predictive maintenance.
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基于预后性能的健康监测传感器的比较研究
在工业厂房或飞机等安全关键系统中,故障在运行过程中不可避免地发生,在保持高可用性的同时防止故障发生非常重要。因此,人们正在努力开发先进的预测算法和传感技术,以实现预测性维护。预测的可靠性和准确性不仅取决于预测算法,还取决于传感器数据的收集。然而,基于预测性能和检测调度对各种传感技术进行评价的研究并不多见。根据传感器在保持其预测性能的同时减少不必要的检查或测量成本的贡献来选择不同的传感器成本是更合理的。因此,作者试图从传感器抗噪声方面全面评估不同传感器的成本效益。通过仿真分析了在不同测量间隔和不同噪声水平下的预测性能。在此基础上,分析了两种不同传感器的实际运行故障(RTF)数据,设计了最优的预测性维修测量系统。
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