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Review
Peer-Review Record

Machine-Learning-Based Methods for Acoustic Emission Testing: A Review

Appl. Sci. 2022, 12(20), 10476; https://doi.org/10.3390/app122010476
by Giuseppe Ciaburro * and Gino Iannace
Reviewer 1: Anonymous
Reviewer 2:
Reviewer 3: Anonymous
Reviewer 4: Anonymous
Appl. Sci. 2022, 12(20), 10476; https://doi.org/10.3390/app122010476
Submission received: 18 September 2022 / Revised: 13 October 2022 / Accepted: 13 October 2022 / Published: 17 October 2022

Round 1

Reviewer 1 Report

The manuscript entitled Machine Learning-based methods for Acoustic Emission Testing: A Review does not present new scientific content in my opinion. The article focuses on the description and various applications of the acoustic emission method in scientific works. Please outline the main research and scientific achievements in the manuscript.

Author Response

The authors thank the reviewer for careful and timely suggestions. Every indication of the reviewer was taken into consideration by modifying the paper in the direction suggested, in this way the presentation of our work is certainly improved.  All the changes made to the paper have been highlighted in yellow in order to allow easier control by the reviewer. The authors made a complete revision of the English of the entire work. In addition, as suggested by the reviewer, they added a summary extracted from the reviewed papers that lists the main points highlighted by the scientific community on the subject. I have renamed section 5 to Summary and Future Trends to emphasize the essential role of this section in outlining the essential points that have come out of this study. In addition, other arguments were added to the conclusions.

Reviewer 2 Report

Dear Authors, Here we only have a review article. You should add at least your more extensive research and compare it with the proposed research from the literature. The introduction should provide an overview of similar studies. On the other hand, the following parts should be based on own research together with a proposal of a statistical hypothesis. Applications should relate to specific results.

Author Response

The authors thank the reviewer for careful and timely suggestions. Every indication of the reviewer was taken into consideration by modifying the paper in the direction suggested, in this way the presentation of our work is certainly improved.  All the changes made to the paper have been highlighted in yellow in order to allow easier control by the reviewer. The authors made a complete revision of the English of the entire work. In addition, as suggested by the reviewer, they added a summary extracted from the reviewed papers that lists the main points highlighted by the scientific community on the subject. I have renamed section 5 to Summary and Future Trends to emphasize the essential role of this section in outlining the essential points that have come out of this study. In addition, other arguments were added to the conclusions.

Reviewer 3 Report

The authors presented the paper “Machine Learning-based methods for Acoustic Emission Testing: A Review” which needs improvements according to following comments:

1.      Why did you write “Machine Learning” with big letters in abstract?

2.      Please be careful in using abbreviations such as AE, AET and organize it better.

3.      Please add a sentence in the abstract what did you find with the proposed approach. You can show the key findings and primary contribution of this method.

4.      Please reconsider this sentence:

 Of great importance is the possibility of using non-destructive ..

5.      The introduction is good, please include the following papers:

“A review of indirect tool condition monitoring systems and decision-making methods in turning: Critical analysis and trends”

“Artificial intelligence systems for tool condition monitoring in machining: Analysis and critical review”

“Indirect monitoring of machining characteristics via advanced sensor systems: a critical review”

6.      Please represent the acoustic emission wave propagation from a body while exposing the external forces with a figure. It will clear the minds during reading the paper.

7.      Conclusions are weak. At least 7-8 items should be added.

8.      Please add future prospects section for explaining the thoughts of the authors for the future studies and expectations.

9.      It may be good to add a nomenclature.

10.   All figures need extra explanations.

11.   At least 20-30 references need to be added for such topic.

Author Response

The authors thank the reviewer for careful and timely suggestions. Every indication of the reviewer was taken into consideration by modifying the paper in the direction suggested, in this way the presentation of our work is certainly improved.  All the changes made to the paper have been highlighted in yellow in order to allow easier control by the reviewer. The authors made a complete revision of the English of the entire work. In addition, as suggested by the reviewer, they added a summary extracted from the reviewed papers that lists the main points highlighted by the scientific community on the subject. I have renamed section 5 to Summary and Future Trends to emphasize the essential role of this section in outlining the essential points that have come out of this study. In addition, other arguments were added to the conclusions.

  1. Why did you write “Machine Learning” with big letters in abstract?

AUTHORS RESPONSE: I have modified each occurrence as suggested by the reviewer

  1. Please be careful in using abbreviations such as AE, AET and organize it better.

AUTHORS RESPONSE: I have modified each occurrence as suggested by the reviewer

  1. Please add a sentence in the abstract what did you find with the proposed approach. You can show the key findings and primary contribution of this method.

AUTHORS RESPONSE: As suggested by the reviewer, a period was added at the end of the abstract to summarize the results.

  1. Please reconsider this sentence:

 Of great importance is the possibility of using non-destructive ..

AUTHORS RESPONSE: Replaced with: Non-destructive methods can be useful

  1. The introduction is good, please include the following papers:

“A review of indirect tool condition monitoring systems and decision-making methods in turning: Critical analysis and trends”

“Artificial intelligence systems for tool condition monitoring in machining: Analysis and critical review”

“Indirect monitoring of machining characteristics via advanced sensor systems: a critical review”

AUTHORS RESPONSE: Thanks for highlighting these works, I added them to the ones already revised.

  1. Please represent the acoustic emission wave propagation from a body while exposing the external forces with a figure. It will clear the minds during reading the paper.

AUTHORS RESPONSE: The figures have been revised and enriched with explanation

  1. Conclusions are weak. At least 7-8 items should be added.

AUTHORS RESPONSE: Additional items were added to the conclusions

  1. Please add future prospects section for explaining the thoughts of the authors for the future studies and expectations.

AUTHORS RESPONSE: Future prospects section was added

  1. It may be good to add a nomenclature.

AUTHORS RESPONSE: Thanks, each term mentioned in the paper has been adequately introduced.

  1. All figures need extra explanations.

AUTHORS RESPONSE: An extra explanations was added to all figures

  1. At least 20-30 references need to be added for such topic.

AUTHORS RESPONSE: More references were added

Reviewer 4 Report

The topic is very interesting and must be a significant contribution to the filed if well reviewed. However, the papers is organized in a extremely unprofessional way. Too wordy about introduction and lots of background introduced is also known to the audience from the community.

Author Response

The authors thank the reviewer for careful and timely suggestions. Every indication of the reviewer was taken into consideration by modifying the paper in the direction suggested, in this way the presentation of our work is certainly improved.  All the changes made to the paper have been highlighted in yellow in order to allow easier control by the reviewer. The authors made a complete revision of the English of the entire work. In addition, as suggested by the reviewer, they added a summary extracted from the reviewed papers that lists the main points highlighted by the scientific community on the subject. I have renamed section 5 to Summary and Future Trends to emphasize the essential role of this section in outlining the essential points that have come out of this study. In addition, other arguments were added to the conclusions.

Round 2

Reviewer 2 Report

Dear Authors,

I still miss specific conclusions with specific data, I still miss a bit of my own experimental research with the proposed statistical hypothesis.

Author Response

The authors further thank the reviewer for the valuable contribution he made to improving the work. As required, a new section has been added in which, starting from data collected by piezoelectric AE sensors, numerous ML algorithms have been applied to classify the signals.

Reviewer 4 Report

This review article still looks not in a concise way, no cutting-edge technology is introduced. Since other reviewers do no have this kind of concern, I still accept it in the present form but not recommend it. It would be great if the author can modify the contents by including more new technology and innovations.

Author Response

The authors further thank the reviewer for the valuable contribution he made to improving the work. As required, a new section has been added in which, starting from data collected by piezoelectric AE sensors, numerous ML algorithms have been applied to classify the signals. In addition, new sections have been added in which technological innovations relating to sensors are listed.

Round 3

Reviewer 2 Report

Requests for concrete results still need to be grouped. Describe these algorithms more clearly.

Author Response

As requested by the reviewer, I proceeded to describe in more detail the algorithms used in the experimental phase of analysis of the AE data. I have also enriched the descriptive part of the results.

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