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Article
Peer-Review Record

Weak Fault Feature Extraction Method Based on Improved Stochastic Resonance

Sensors 2022, 22(17), 6644; https://doi.org/10.3390/s22176644
by Zhen Yang 1, Zhiqian Li 2, Fengxing Zhou 1, Yajie Ma 1 and Baokang Yan 1,*
Reviewer 1:
Reviewer 2:
Sensors 2022, 22(17), 6644; https://doi.org/10.3390/s22176644
Submission received: 28 July 2022 / Revised: 19 August 2022 / Accepted: 25 August 2022 / Published: 2 September 2022
(This article belongs to the Special Issue Advanced Sensor Fault Detection and Diagnosis Approaches)

Round 1

Reviewer 1 Report

1. In Section 2, how is Eq. (2) derived? This is the basis for the research content of this paper, and a detailed derivation should be given. Similarly, Eq. (5) is the output SNR for an overdamped SR system, but not for an underdamped SR system. The output SNR corresponding to Eq. (1) should be provided in the paper. Therefore, some conclusions based on Eq. (5) are also unconvincing in this case.

2. What does the variable e in Eq. (13) represent?

3. Only the parameters γ and ε are optimized in this paper, and the parameter R only gives the value range; in this case, how to determine the optimal value of R?

4. The method for determining the index CEI is very similar to the method in the literature "Novel synthetic index-based adaptive stochastic resonance method and its application in bearing fault diagnosis", which fails to reflect the highlights of the research work in this paper.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

comments are attached.

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

I have no other comments.

Reviewer 2 Report

The manuscript was modified according to questions.

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