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Article
Peer-Review Record

Failure Detection of Laser Welding Seam for Electric Automotive Brake Joints Based on Image Feature Extraction

Machines 2025, 13(7), 616; https://doi.org/10.3390/machines13070616
by Diqing Fan *, Chenjiang Yu, Ling Sha, Haifeng Zhang and Xintian Liu
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Machines 2025, 13(7), 616; https://doi.org/10.3390/machines13070616
Submission received: 15 June 2025 / Revised: 8 July 2025 / Accepted: 14 July 2025 / Published: 17 July 2025

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper addresses an industrially relevant topic and presents a detailed technical approach. The methodology is generally sound, and the application of machine vision to weld defect detection is well motivated.

However, the manuscript requires improvements in several areas:

  • English language needs revision to improve clarity.
  • Introduction should highlight the novelty of the work.
  • In the methods section, more clarity on classifier training is needed.
  • Figures and tables need better quality and proper referencing.
  • The results should include clearer summaries and comparisons with existing methods.
  • The conclusion should better discuss limitations and future work.

 

Comments on the Quality of English Language

The English needs improvement, as there are several grammatical errors and some unclear sentences. The style would benefit from clearer structure, more concise wording, and more consistent technical terminology to improve overall readability.

Author Response

请参阅附件。

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

It appears that Eq. 15 needs to be corrected.

The test set consists of images with 3 kinds of defects. The results look very optimistic. Most cases were recognized and classified correctly, and only a few were missed. That is good, but in my opinion, the analysis could also be extended to cases including non-defect images. Then, the classifier will work with harder situations and more quality indicators, like 'false negatives' and 'false positives' or similar, are available. If not, the ability of the system is reduced to classify one of the categories, but what about the initial aim, as detecting the flaw or saying no defect detected? Generally, I suggest providing more details on the analysis and results. This remark is for the authors' decision. 

 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

The authors introduced the failure detection of laser welding seam for electric automotive brake joints,unfortunately, most of the content is about the popularization for failure detection of laser welds. Although there are some experiments and analyses in the main text, the content is relatively scarce. Overall, this manuscript is far from meeting the requirements of articles in international journals, it is recommended to reject. The main problems of manuscript are as flows:

(1) The abstract fails to reflect the experimental methods and main conclusions of the manuscript. It is suggested to be rewritten.

(2) The introduction fails to fully present the current research status.

(3) The experimental procedures are not elaborated sufficiently.

(4) The pictures are too blurry to distinguish, and lacks a scale.

(5) The conclusion is suggested to be rewritten.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

As the authors comprehensively revised the manuscript in accordance with the reviewers' comments, the reviewer agreed to accept the manuscript.

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