Application of Reduced Order Surrogate Models in Compatible Determination of Material Properties Profiles by Eddy Current Method
and Nataliia Tychkova 1
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThis paper proposed an approach to simultaneously determining the distributions of electrical conductivity and magnetic permeability However, I have some additional comments for the authors:
1. In the introduction, the authors should indicate some specific application scenarios using proposed method.
2. In experiments, it is suggested that the authors could give an application case of the proposed measurement method so as to verify the superiority to other traditional measurement, The proposed algorithm is compared with the electromagnetic parameter decoupling algorithms in recent years, such as 10.1109/JSEN.2020.3038203, 10.1109/I2MTC53148.2023.10176103
3. In theoretical analyses, it is necessary to give a schematic figure of the test object in order to understand the relevant derivations.
4. “the maximum relative error of amplitude and phase in determining the vector potential did not exceed 0.2 % and 0.5 %, respectively.” It is necessary to give a graph of the results of the calculations and to analyze the reasons for the errors in the calculations.
5. Highlight the innovation of the paper.
Comments for author File: 
Comments.pdf
Author Response
Dear Reviewer,
thank you for your efforts and constructive comments. Our responses are in the attached file.
Sincerely, the Authors.
Author Response File: Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsIn this paper, a method based on the use of surrogate optimization is proposed to determine the distributions of electrical conductivity and magnetic permeability in planar. The method also involves the use of a high performance neural network proxy model. The content of paper is useful and interesting. However, significant modification is needs.
1) First of all language should be improved.
2) The introduction should be shorted and improved. The contribution of the paper should be highlighted.
3) The structure of paper should be improved. It seems that no real sample is used. Only simulation results were used?
4) The diagram of the proposed algorithm should be added.
5) The finally obtained distribution should be shown to validate the algorithm.
Comments on the Quality of English LanguageThe quality of language should be improved.
Author Response
Dear Reviewer,
thank you for your efforts and constructive comments. Our responses are in the attached file.
Sincerely, the Authors.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThis manuscript investigates the use of reduced order surrogate models to determine material characteristic profiles in eddy current methods. The manuscript introduces the use of proxy optimization techniques and principal component analysis (PCA) spatial dimensionality reduction in electromagnetic non-destructive testing to process high-dimensional search spaces, thereby improving the efficiency and accuracy of material property profile reconstruction. This manuscript should be revised for the following issues before being considered for publication.
1. The manuscript mentions various dimensionality reduction methods such as PCA, KPCA, Autoencoders, and VAEs, but does not provide a detailed explanation of why these methods were chosen, as well as their respective advantages and limitations. Suggest adding a discussion on the selection criteria for dimensionality reduction methods.
2. In order to comprehensively evaluate the effectiveness of the selected dimensionality reduction method, it is recommended to increase comparative experiments with other dimensionality reduction methods, such as t-SNE, U-Map, etc., to highlight the advantages of the selected method. The manuscript mentions the use of neural networks for prediction, but does not provide a detailed explanation of the structure and parameter settings of the neural network. Suggest optimizing the neural network structure, such as adding hidden layers, adjusting the number of neurons, etc., to improve prediction accuracy.
3. In addition to the dimensionality reduced features, it is possible to consider introducing more features related to material properties to improve the generalization ability of the model. Data preprocessing is crucial for model performance. Suggest further preprocessing of the raw data, such as denoising, standardization, etc., to improve data quality.
4. The manuscript mainly focuses on the electrical and physical properties of metallic materials, and it is recommended to extend to other types of materials such as non-metallic and composite materials to verify the universality of the method.
5. In addition to numerical simulation, it is recommended to add experimental verification to validate the accuracy of model predictions through actual measurements. The analysis of the results in the manuscript is relatively general. It is recommended to conduct a more detailed analysis of the results, such as comparing and discussing the predicted results under different materials and conditions.
6. In order to better showcase the research results, it is recommended to add visualization methods such as 3D graphics, heat maps, etc., to present data features and model performance more intuitively.
7. In the conclusion section, in addition to summarizing the research results, it is recommended to clarify future research directions, such as exploring new dimensionality reduction methods, optimizing neural network structures, expanding application scope, etc., to promote the development of related fields. When summarizing research results, it is recommended to emphasize the universality and generalizability of the method to attract more researchers' attention and application of the method.
Author Response
Dear Reviewer,
thank you for your efforts and constructive comments. Our responses are in the attached file.
Sincerely, the Authors.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsThe authors have revised it according to my request, and I think it can be published.
Comments on the Quality of English LanguageI have no further comments.
Reviewer 2 Report
Comments and Suggestions for AuthorsAll comments were dealt well. The manuscript is acceptable.
Reviewer 3 Report
Comments and Suggestions for AuthorsThe overall response is clear and the problem has been effectively resolved and responded to. I think the current version can be accepted for publication.
Comments on the Quality of English LanguageFine
