Study on Vibration-Transmission-Path Identification Method for Hydropower Houses Based on CEEMDAN-SVD-TE
Round 1
Reviewer 1 Report
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Comments for author File: 
Comments.pdf
Author Response
Response to Reviewer 1 Comments
Point 1: The novelties of the proposed work are not completely clear.
Response 1: Thank you very much for your professional advice. Based on your suggestion, we have revised the highlight, introduction, and conclusion sections of the paper to further explain the innovation points of the paper in order to facilitate the reader to understand the main innovative points more clearly. The main innovations of the article are summarized as follows.
(1) In the background that the vibration problem of hydropower house is drawing more and more attention and the vibration response of hydropower house structure is difficult to identify effectively, this paper analyzes the advantages and disadvantages of CEEMDAN, SVD and TE in the field of signal processing, and innovatively proposes the method of CEEMDAN-SVD-TE that can effectively utilize the advantages of each method. With the help of simulation signals, it is verified that the CEEMDAN-SVD-TE method has higher effectiveness and superiority than the single TE algorithm in information transmission direction identification.
(2) On the basis of clarifying the effectiveness of CEEMDAN-SVD-TE in information transmission direction identification, the method is innovatively applied to a large hydropower station. Based on the CEEMDAN-SVD-TE, the vibration response due to tailwater fluctuation is analyzed, and it is found that the vibration transmission paths of the hydropower house under different working conditions is tailwater pipe (top cover measurement point)→turbine pier (stator foundation measurement point, lower frame foundation measurement point)→generator floor (generator floor measurement point).The transmission path identification method of CEEMDAN-SVD-TE provides a new method and innovative perspective for the analysis of vibration response and vibration mechanism in hydraulic structures.
(3) With the help of the information transmission rate based on transfer entropy, this paper quantitatively describes the transmission feature of the vibration information and identifies that the lower frame foundation, as the main load-bearing member of the hydropower house, is an important node in the vibration transmission of the house and a key factor for optimal design of vibration isolation in the hydropower house. This research provides a theoretical basis for identification of vibration transmission paths in hydropower house, offers an essential reference for the optimal designing and damping of the house, and suggests a new idea for structural vibration monitoring and safety management of hydropower station.
Point 2: The bibliography list must be enriched by adding more recent references.
Response 2: Thank you very much for your professional advice. We have studied the articles in the relevant areas of this paper extensively and selected some more appropriate and recent references to enrich the bibliography list, the specific changes are marked in red in the text.
Point 3: Read again the text to correct the residual typing and language errors.
Response 3: Thank you very much for your professional advice. We have revised and improved the typing and language of the entire manuscript to meet the standards of the journal. The specific changes are marked in red in the text.
Point 4: Some new results must be given also in tabular form in order to better understand the differences and to facilitate the work of future scientists interested in possible comparisons.
Response 4: Thank you very much for your professional advice. To further facilitate the researcher to understand the main results obtained by the method in this paper more clearly, the information transmission rate between the main measurement points under three conditions is produced in Table 7. This table will further facilitate the researcher to realize the descriptions in the result and conclusion, present the differences in the vibration pattern of the hydropower house under each operating condition, and create a basis for future research results that can be compared.
Point 5: The manuscript would also benefit from a thorough validation and comparisons to experimental data accounting for uncertainties.
Response 5: Thank you very much for your professional advice. With your suggestion, we have further revised the expressions in the text.
To ensure the validity of the article results, we have firstly verified the validity of the CEEMDAN-SVD-TE method in Simulation Analysis. In section 3.1, the advancedness of CEEMDAN-SVD in the field of filtering signal noise and extracting signal features is verified with the help of simulation signals; in section 3.2, the effectiveness of transfer entropy in information transmission direction identification is verified by analyzing the change on transfer entropy and information transmission rate of two correlated signals under different correlation coefficients; in section 3.3, by comparing the analysis results on the transfer entropy of the noisy simulation signal before and after CEEMDAN-SVD denoising, it is proved that the CEEMDAN-SVD-TE method is more effective and accurate than the TE algorithm in information transmission direction identification.
Based on the above research, the CEEMDAN-SVD-TE method is applied to a large hydropower house. By comparing the transfer entropy between measurement points under different operation conditions, the vibration transmission path of the hydropower house is derived as tailwater pipe (top cover measurement point)→turbine pier (stator foundation measurement point, lower frame foundation measurement point)→generator floor (generator floor measurement point). The transmission path identification method of CEEMDAN-SVD-TE provides a new method and innovative perspective for the analysis of vibration response and vibration mechanism in hydraulic structures.
Point 6: Source of Equation (1) and Equation (8) is missing
Response 6: Thank you very much for your professional advice. To address the problem that sources of Equations are missing, we have read extensively and cited some important supporting articles in the Equations.
We are grateful for your constructive comments. We tried our best to improve the manuscript and made some changes in the revised version. These changes will not influence the content and framework of the paper. Here we did not list the changes but marked them in the revised version with red.
We deeply appreciate your work, and hope that the correction will meet with approval.
Once again, thank you very much for your comments and suggestions.
Yours sincerely
Ziyu Li
Corresponding author:
Name:Ziyu Li
E-mail: [email protected]
Author Response File: 
Author Response.docx
Reviewer 2 Report
The paper entitled “Study on Vibration Transmission Path Identification Method for Hydropower House Based on CEEMDAN-SVD-TE” presents research on using a combined empirical mode decomposition, denoising, and transfer entropy algorithm for the analysis of the transmission path for a hydropower house. It is found that the proposed approach can effectively extract the frequency information of the signals and identify the information transmission between them, therefore providing useful insights into the vibration information. The results are compared under different operation conditions. Overall, I believe the current work provides a useful approach for the analysis of hydropower houses. The manuscript is somewhat lengthy, but the authors did a good job of organizing different sections and presenting the results. I only have a few minor comments for the authors to consider.
(1) The analysis method (CEEMDAN-SVD-TE) appears in section 1. However, the abbreviations SVD (singular value decomposition) and TE (transfer entropy) are introduced in lines 194 and 221, respectively. They need to be described as they appear for the first time in the manuscript.
(2) The transfer entropy simulation (section 3.2) is a bit confusing. For example, how is the correlation coefficient \mu manifested? Also, why is it set to 0.2, 0.4, 0.6, and 0.8? It is also not clear why the y-axis has a unit of bit.
Author Response
Response to Reviewer 2 Comments
Point 1: The analysis method (CEEMDAN-SVD-TE) appears in section 1. However, the abbreviations SVD (singular value decomposition) and TE (transfer entropy) are introduced in lines 194 and 221, respectively. They need to be described as they appear for the first time in the manuscript.
Response 1: Thank you very much for your professional advice. We have revised the introduction of the article and added the abbreviations SVD (singular value decomposition) and TE (transfer entropy).
Point 2: The transfer entropy simulation (section 3.2) is a bit confusing. For example, how is the correlation coefficient manifested? Also, why is it set to 0.2, 0.4, 0.6, and 0.8? It is also not clear why the y-axis has a unit of bit.
Response 2: Thank you very much for your professional advice.
(1) We have perfected and supplemented the transfer entropy simulation (section 3.2) with a purpose to improve the legibility of the article. The modified section 3.2 is shown below in simplified form.
(1)
(2)
As shown in equations (1-2), it can be seen that the signal consists of the signal with correlation coefficient and part of the interference signal. From the perspective of the signal composition, as the correlation coefficient increases, the proportion of signal in signal increases and the proportion of interference signal decreases, the signal should be more easily considered as the source of signal.
On the basis of this, we identifies the applicability of transfer entropy in the direction identification and quantitative analysis of transfer effects between signals by varying the correlation coefficient in the signal and analyzing the changes in and with different correlation coefficients . The correlation coefficients of signals and are set to 0.2, 0.4, 0.6, and 0.8, respectively, and the transfer entropy and between the simulated signals and are calculated.
The simulation results indicate that the transfer entropy is highly sensitized to the transmission direction of the information flows between two signals, and the transfer entropy curve can accurately reflect the direction of information transmission between two signals. increases with the increasing correlation coefficient , which is consistent with the correlation of the constructed signals, indicating that the transfer entropy can not only reflect the directionality of information transmission between two signals, but also accurately quantify the correlation degree between the two signals from the perspective of entropy.
(2) Transfer entropy is developed and proposed on the basis of information entropy[1]. In 1948, Shannon[2] introduced the concept of entropy in statistical physics into the process of channel communication, which was defined as information entropy. Information entropy is the average value of the information contained in each message accepted. It measures the uncertainty of information. The greater the entropy is, the more random distribution of information sources is. Mathematically, information entropy is actually the expectation of the amount of information, so the unit of information entropy is bit. On the basis of this, the unit of transfer entropy is bit too.
Following your suggestion, we have added a description of the units for transfer entropy in section 2.3.
[1] Schreiber, T. Measuring information transfer. Physical Review Letters. 2000, 85(2): 461.
[2] Shannon, C. E. A mathematical theory of communication. The Bell system technical journal. 1948, 27(3), 379-423.
We are grateful for your constructive comments. We tried our best to improve the manuscript and made some changes in the revised version. These changes will not influence the content and framework of the paper. Here we did not list the changes but marked them in the revised version with red.
We deeply appreciate your work, and hope that the correction will meet with approval.
Once again, thank you very much for your comments and suggestions.
Yours sincerely
Ziyu Li
Corresponding author:
Name:Ziyu Li
E-mail: [email protected]
Author Response File: Author Response.docx
