Due to complicated noise interference, seismic signals of high arch dam are of non stationarity and a low signal-to-noise ratio\n(SNR) during acquisition process. The traditional denoising method may have filtered effective seismic signals of high arch dams.\nA self-adaptive denoising method based on ensemble empirical mode decomposition (EEMD) combining wavelet threshold with\nsingular spectrum analysis (SSA) is proposed in this paper. Based on the EEMD result for seismic signals of high arch dams, a\ncontinuous mean square error criterion is used to distinguish high-frequency and low-frequency components of the intrinsic\nmode functions (IMFs). Denoised high-frequency IMF using wavelet threshold is reconstructed with low-frequency components,\nand SSA is implemented for the reconstructed signal. Simulation signal denoising analysis indicates that the proposed method can\nsignificantly reduce mean square error under low SNR condition, and the overall denoising effect is superior to EEMD and\nEEMD-Wavelet threshold denoising algorithms. Denoising analysis of measured seismic signals of high arch dams shows that the\nperformance of denoised seismic signals using EEMD-Wavelet-SSA is obviously improved, and natural frequencies of the high\narch dams can be effectively identified.
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