Next Article in Journal
Machine Learning in Assessing Canine Bone Fracture Risk: A Retrospective and Predictive Approach
Previous Article in Journal
An Interactive Transient Model Correction Active Sonar Target Tracking Method
 
 
Article
Peer-Review Record

PMT Fluorescence Signal Denoising Processing Based on Wavelet Transform and BP Neural Network

Appl. Sci. 2024, 14(11), 4866; https://doi.org/10.3390/app14114866
by Jiehui Liu 1,2, Yunhan Zhang 1,2,3, Jianshen Li 1,2,*, Yadong Zhao 3, Jinxi Guo 1,2, Lijie Yang 1,2 and Haichao Zhao 4
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Appl. Sci. 2024, 14(11), 4866; https://doi.org/10.3390/app14114866
Submission received: 1 May 2024 / Revised: 1 June 2024 / Accepted: 2 June 2024 / Published: 4 June 2024

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This article proposes a signal denoising and detection framework for sulfur  dioxide concentration with PMT. The methodology and experiments are clearly explained. My main concerns are listed as follows.

1. The main novelty is the signal processing scheme. However, it is actually the combination of wavelet denoising and BP neural network detection. These algorithms have been widely used in the past years. The introduction of existing detection methods and main contributions of this article should be      explained.

2. Why is the BP neural network selected? The comparison with other algorithms can be present.

3. Does the wavelet denoising affect the final detection accuracy. As the neural network can automatically learn the signatures, the detection results before and after applying the wavelet denoising can be compared.

4. The introduction part of this article should describe the development of sulfur dioxide concentration detection and the motivation of this work.

5. The numbering of section 2 is not correct. The quality of some figures can be improved.

Comments on the Quality of English Language

NA

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Review of manuscript entitled “PMT fluorescence signal denoising processing based on wavelet transform and BP neural network” by Jiehui Liu et al.

The manuscript shows the following sections:

2. Detection system section, 2.1 Optical path section, 2.2 Circuit section, 3 Wavelet transform, 4 Temperature drift of PMT, 4-1 Data collection, 4-2 Data processing, 5 Experimental verification and 6 Conclusions.

Regarding the section 2.1 Optical path, Fig. 1 shows the Workflow diagram. It is necessary to show a detailed diagram showing the position of optical components and the PMT. Also the diagram should show the beam’s path and the different optical elements should have names. Show a diagram of the “reaction chamber” included the PMT.

It is mentioned the “flat convex lenses”. Describe these lenses and preferably use the optics language. Are they zone plate lenses?. Possibly they are positive lenses. Show in the new diagram the way they are placed in the optical path.   

In the first paragraph of section 5 it says ”If methane an hydrogen sulfide, and nitrous oxide are present in the gas, their effect on the determination of sulfur dioxide is minimal”. Give a reference for this statement or explain why this happen.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Back to TopTop