###### Abstract
It is an effective tool for analyzing smooth signals but cannot correct and analyze local distortion of the signal. A digital filter is an improved Fourier-transform-based denoising method, which achieves denoising by mathematical operations on the difference equations of a discrete signal, but requires predefined technical specifications such as a passband cutoff frequency and stopband cutoff frequency [13; 14]. The wavelet transform allows local transformation of the time and frequency of the signal, but there is no standard available for choosing the wavelet base function [15]. Empirical mode decomposition (EMD) is an adaptive signal-analyzing method for processing nonlinear and non-stationary signals [16; 17]. [PERSON] [18] introduces the application of the EMD method in complex vibration signal processing and modal identification of civil structures in detail. However, due to the defects of his computational theory, the decomposition process of EMD may cause boundary effects and mode mixing [19; 20]. In order to reduce the interference of the mode mixing, the ensemble empirical mode decomposition (EEMD) method is proposed [21]. [PERSON] [22] uses the EEMD method to effectively reduce the background noise of airframe-vibration data obtained from aircraft water-landing experiments. [PERSON] [23] uses the EEMD method to extract weak fault signals from bearing vibration signals to achieve early bearing fault prediction. However, the effect of EEMD decomposition depends on the integration time and the amplitude of the added white noise [24]; the mode-mixing phenomenon will not be mitigated if the parameters are not chosen properly. With the purpose of overcoming the above problems, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is proposed. This method adds adaptive white noise at each stage of the decomposition and calculates a unique residual signal for each mode component, which results in negligible reconstruction error [25; 26]. [PERSON] [27] applies CEEMDAN to bridge structural vibration signal processing to effectively identify the location and extent of bridge damage. However, although CEEMDAN can effectively decompose the signal and obtain the characteristic mode components, it cannot effectively filter out high-frequency white noise due to background noise [28]. Singular value decomposition (SVD), as a typical orthogonal decomposition denoising method, can efficiently filter out high-frequency noise in the signal [29]. As the problem of vibration in a hydropower house has become a subject of increasing concern, researchers have started to analyze vibration from the perspective of the vibration mechanism and have tried to explore the energy-transfer path of vibration in a hydropower house. [PERSON] [30] studies the power transmission between the underground main powerhouse and auxiliary powerhouse based on the tidal current theory. They find that the vibration-transfer direction of the underground plant is mainly perpendicular to and along the flow direction of the bedrock. [PERSON] [31] concludes that the transmission of transverse vibration was larger than that of longitudinal and vertical vibration, while the transmission intensity of low-frequency vibration and rotational frequency vibration were basically equal. [PERSON] [32] carries out the calculation of structural sound intensity based on finite element theory for different parts of the hydropower plant, and realizes the vector visualization of the transmission path. Researchers often study the vibration of the hydropower house through numerical model calculations and have achieved good results, but the shortcomings and challenges cannot be ignored. Most previous studies have used computational analysis methods that assume the excitation of the house is usually composed of steady-state harmonic loads, which simplifies mathematical calculations but adds human interference. In the field of vibration response analysis with the help of structural monitoring data, the transfer entropy (TE) has been widely used.