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首页> 外文期刊>Advances in Mechanical Engineering >A research on fiber-optic vibration pattern recognition based on time-frequency characteristics:
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A research on fiber-optic vibration pattern recognition based on time-frequency characteristics:

机译:基于时频特性的光纤振动模式识别研究:

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摘要

To detect and recognize any type of events over the perimeter security system, this article proposes a fiber-optic vibration pattern recognition method based on the combination of time-domain features and time-frequency domain features. The performance parameters (event recognition, event location, and event classification) are very important and describe the validity of this article. The pattern recognition method is precisely based on the empirical mode decomposition of time-frequency entropy and center-of-gravity frequency. It implements the function of identifying and classifying the event (intrusions or non-intrusion) over the perimeter to secure. To achieve this method, the first-level prejudgment is performed according to the time-domain features of the vibration signal, and the second-level prediction is carried out through time-frequency analysis. The time-frequency distribution of the signal is obtained by empirical mode decomposition and Hilbert transform and then the time-frequency entropy and.
机译:为了检测和识别外围安全系统中的任何类型的事件,本文提出了一种基于时域特征和时频域特征相结合的光纤振动模式识别方法。性能参数(事件识别,事件位置和事件分类)非常重要,它们描述了本文的有效性。模式识别方法正是基于时频熵和重心频率的经验模式分解。它实现了对周边事件进行识别和分类(入侵或非入侵)以确保安全的功能。为了实现该方法,根据振动信号的时域特征进行了第一级预测,并通过时频分析进行了第二级预测。信号的时频分布是通过经验模态分解和希尔伯特变换,然后是时频熵得到的。

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