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A Survey on Signal Processing Methods in Fiber Optic Sensor for Oxidized Carbon Steel

机译:氧化碳钢光纤传感器信号处理方法调查

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This paper provides a broad overview of the adaptive methods for noise reduction used in the analysis of data in the different sensors such as acoustic emissions sensors, power quality signal analysis. The two algorithms are the Empirical Mode Decomposition and the Ensemble Empirical Mode Decomposition. We selected these two algorithms because our focus is on these methods. Firstly, this paper exhibits the inner workings of each algorithm both in the original authors' intuition and the mathematical model utilized. Next, we discuss the advantages of each of the algorithms based on recent and credible research papers and articles. We also critically dissect the limitations of each algorithm. This paper aims to give a general understanding on these algorithms which we hope will spur more research in improving the field of signal processing in the fiber optic sensor for the oxidised carbon steel.
机译:本文概述了用于分析不同传感器等隔音传感器,电源质量信号分析的数据分析的噪声降低的自适应方法。这两个算法是经验模式分解和集合经验模式分解。我们选择了这两个算法,因为我们的重点是在这些方法上。首先,本文在原作者的直觉和所使用的数学模型中表现出每种算法的内部工作。接下来,我们讨论了每个算法的每个算法的优点,基于最近和可信的研究论文和文章。我们还严格解剖每个算法的局限性。本文旨在对这些算法进行一般性的理解,我们希望在改善氧化碳钢中改善光纤传感器中的信号处理领域。

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