The invention discloses a CEEMDAN-Grey-SSA weak signal extraction method, and the method comprises the steps: carrying out the complete adaptive noise ensemble empirical mode decomposition CEEMDAN decomposition of obtained vehicle body offset data, obtaining K IMF component signals, taking IMF1 (t) as a component mainly containing noise, calculating the gray correlation degree of the remaining IMF components and the IMF1 (t) to represent the noise level of the IMF components, and carrying out the calculation of the gray correlation degree of the remaining IMF components and the IMF1 (t). Carrying out descending order arrangement; building a gray model, then performing soft threshold noise reduction processing, and then performing reconstruction with an IMF component with dominant effective signals; and secondary noise reduction is carried out based on singular spectrum analysis SSA, and the train body transverse movement amount caused by track horizontal irregularity in the collected low-signal-to-noise-ratio train offset is obtained. According to the method, time-frequency analysis is carried out on the signals, and effective signals can be accurately extracted, so that weak signals can be extracted under the condition of low signal-to-noise ratio.
本发明公开了一种CEEMDAN‑Grey‑SSA弱信号提取方法,首先对获取得到的车体偏移数据进行完全自适应噪声集合经验模态分解CEEMDAN分解,得到K个IMF分量信号,将IMF1(t)视为主要包含噪声的分量,因此计算剩余IMF分量与IMF1(t)的灰色关联度表征IMF分量的噪声水平,并进行降序排列;搭建灰色模型,然后进行软阈值降噪处理,然后与有效信号占主导的IMF分量进行重构;基于奇异谱分析SSA进行二次降噪,得到采集的低信噪比列车偏移量中由于轨道水平不平顺导致的车体横移量。本发明通过对信号进行时频分析,可对有效信号进行准确提取,以便在低信噪比的情况下进行弱信号的提取。
CEEMDAN-Grey-SSA weak signal extraction method
CEEMDAN-Grey-SSA弱信号提取方法
2023-09-08
Patent
Electronic Resource
Chinese
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