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Peer-Review Record

Chatter Monitoring of Machining Center Using Head Stock Structural Vibration Analyzed with a 1D Convolutional Neural Network

Sensors 2022, 22(14), 5432; https://doi.org/10.3390/s22145432
by Kwanghun Jeong 1, Yeonuk Seong 1, Jonghoon Jeon 1, Seongjun Moon 2 and Junhong Park 1,*
Reviewer 1:
Reviewer 2: Anonymous
Sensors 2022, 22(14), 5432; https://doi.org/10.3390/s22145432
Submission received: 21 June 2022 / Revised: 15 July 2022 / Accepted: 18 July 2022 / Published: 20 July 2022
(This article belongs to the Section Physical Sensors)

Round 1

Reviewer 1 Report

The paper is interesting but there are some issues that must be improved. The main is related to the innovation content of the research. Please motivate how the proposed approach is different from the ones already used based on convolutional neural networks. For spindle speed a wide range of values was used. Please provide a motivation for this choise.

In the conclusions, the authors affirm that the proposed approach allows a real-time chatter detection using a raspberry PI4 board . Please provide computational costs and timing diagrams, also respect to other existing algorithms, to asses the effective real-time applicability of proposed method

 

Other minor issues are:

Raw 14: "cestrum" should be cepstrum

Raw 207: remove space "rep resents"

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report


Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

C1

row 520: with 0.1s of computational the use  "Real-time" adjective it is not correct, please replace "real-time" with "near real-time" as you  introduce a time delay for feedback and control purposes.

Author Response

We replaced "real-time" with "near real-time".

Author Response File: Author Response.pdf

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