Multi-Sensor Information Based Remaining Useful Life Prediction With Anticipated Performance
Multi-Sensor Information Based Remaining Useful Life Prediction With Anticipated Performance
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DOI：
10.1109/tr.2013.2241232
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发表时间：
2013-02
影响因子：
5.9
通讯作者：
Muheng Wei;Maoyin Chen;Donghua Zhou
中科院分区：
文献类型：
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作者：
Muheng Wei;Maoyin Chen;Donghua Zhou
对于一类具有潜在退化的多传感器动态系统，本文主要考虑了具有预期性能的剩余使用寿命预测问题。首先采用基于多传感器观测值的分布式融合滤波递归识别隐退化过程；在此基础上，基于收敛退化状态和运行过程中的参数更新，预测了剩余使用寿命分布。分析了不确定性指数，定量评价了增加多传感器信息对预测剩余使用寿命的效益，并讨论了满足方差等预期性能的传感器选择。通过数值算例和铣床实验实例验证了本文的主要结果。
For a class of multi-sensor dynamic systems subject to latent degradation, the remaining useful life prediction with anticipated performance is mainly considered in this paper. The hidden degradation process is first identified recursively by adopting distributed fusion filtering based on observations from multiple sensors. Then the remaining useful life distribution is predicted on the basis of converged degradation state and parameter updating during the operating process. The uncertainty index is aanalyzed to quantitatively evaluate the benefits of increasing multi-sensor information for predicted remaining useful life, and the sensor selection is also discussed for satisfying the anticipated performance such as variance. Our main results are verified by a numerical example, and a practical case study of the milling machine experiment.