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An Improved EMD Method for Time–Frequency Feature Extraction of Telemetry Vibration Signal Based on Multi-Scale Median Filtering

机译:基于多尺度中值滤波的遥测振动信号时频特征提取改进EMD方法

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摘要

We hereby propose an Empirical Mode Decomposition (EMD) method improved with a multi-scale median filtering for extraction of the time–frequency feature of telemetry vibration signals under interference from impulse noise. The signal is decomposed into a series of intrinsic mode functions (IMF) by EMD roughly. Median filtering is then performed on each IMF with filter window length varying with the IMF’s frequency, respectively. This maneuver will allow effective impulse noise suppression with minimal loss of signal integrity. A new signal can then be reconstructed by adding up each component after the median filtering and treated with a repeat EMD to obtain new IMFs as a final result. This method overcomes the filtering window length selection problem in the median filtering, which can obtain better time–frequency feature extraction performance under the impulse noise interference condition. Data processing results from both a simulation signal and a telemetry vibration signal of a test showed the effectiveness of this method.
机译:我们在此提出一种改进的经验模式分解(EMD)方法,该方法经过多尺度中值滤波,可提取脉冲噪声干扰下遥测振动信号的时频特征。信号被EMD大致分解为一系列固有模式函数(IMF)。然后,对每个IMF进行中值滤波,滤波器窗口长度分别随IMF的频率而变化。该操作将允许有效的脉冲噪声抑制,而信号完整性的损失最小。然后,可以通过在中值滤波之后将每个分量相加来重建新信号,并用重复的EMD处理以获得新的IMF作为最终结果。该方法克服了中值滤波中的滤波窗口长度选择问题,在脉冲噪声干扰条件下可以获得较好的时频特征提取性能。测试的模拟信号和遥测振动信号的数据处理结果表明了该方法的有效性。

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