Bearing-Fault-Feature Enhancement and Diagnosis Based on Coarse-Grained Lattice Features
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThe authors propose a method utilizing coarse-grained lattice features to enhance and diagnose rolling bearing faults effectively. While the manuscript provides detailed content, there are still several issues that need to be addressed.
(1) In the introduction, the authors lack analysis of recent research findings and depth, and fail to introduce the application of deep learning methods in the relevant field. For example, Data-driven lithium-ion batteries capacity estimation based on deep transfer learning using partial segment of charging/discharging data. Energy.
(2) The font size in figures 2 and 3 is too small, making them difficult to read. It is recommended that the authors make adjustments.
(3) When analyzing the proposed method, the authors should focus on highlighting its advantages and provide detailed pseudocode for the calculation process.
(4) When conducting experimental analysis, it is advisable for the authors to employ a variety of state-of-the-art methods for comparative analysis and provide quantified results for comparison. It is recommended to present the comparisons in tables.
(5) The fault diagnosis accuracy of various methods listed by the authors currently exceeds 90%, which already meets the practical engineering requirements. Therefore, it is suggested that the authors analyze the specific advantages of the proposed method.
(6) The conclusion lacks quantitative metrics. It is suggested that the authors revise the conclusion.
(7) There are some grammar and tense issues throughout the paper. It is recommended that the authors thoroughly review and correct these problems.
Comments on the Quality of English LanguageModerate editing of English language required
Author Response
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Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThis study proposed a novel method of enhancing and diagnosing rolling bearing faults based on coarse-grained lattice features. The public datasets and the laboratory data were used to validate the feasibility and effectiveness of the proposed method. This study has certain innovation and engineering application value, and the overall presentation of the paper is clear. The following issues require the authors’ modification or explanation.
1) Whether CGLF is applied in other fields? If so, please make a supplementary introduction in the research status at home and abroad.
2) The symbols in the formulas should be consistent with those in the text, including italics.
3) Step 2 appears on line 134, but no preceding step 1 is found?
4) In Equation 5, does Fcn represent the same variable or function on the left and right sides? If not, use a different symbol.
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThe article submitted for review "Bearing-Fault-feature Enhancement and Diagnosis Based on Coarse-Grained Lattice Features" is an interesting scientific work in the field of application of modern intelligent data processing algorithms for troubleshooting moving systems and objects. In particular, the authors consider the possibility of intelligent troubleshooting of bearings.
As some comments, the following questions can be highlighted?
1) The introduction explores the topic and the degree of its elaboration in sufficient depth. However, the introduction should end with a statement of the purpose and objectives of the study, the solution of which will achieve this goal. It is better to omit the description of the results obtained in Conclusion.
2) In paragraph 4.2 of the article, the authors indicate the sampling frequency of the signals at 16384 Hz. This raises a number of questions:
2.1) Why is this particular sampling rate chosen? In other words, why didn't the authors repeat the previous frequency of 12,000 Hz.
2.2) In Figure 10, the right column has a dimension up to 10000 Hz, although the BP can only give half of 16384 Hz.
3) In conclusion, it is worth pointing out the advantages of the method proposed by the authors over the existing ones, while relying on the numerical indicators announced in Table No. 4.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsI have appreciated the deep revision of the contents and the present form of this manuscript. All my previous concerns have been accurately addressed.
Comments on the Quality of English LanguageModerate editing of English language required
