Sustainable Analysis of Insulator Fault Detection Based on Fine-Grained Visual Optimization

Round 1

Reviewer 1 Report

1. The organize structure of the manuscript is very unreasonable, must major correction.

2. introduction keeps too many empty words, does not focus on the title.

3. some common knowledge should be deleted.

4. Authors should review current study of High-speed railway insulator fault, and explain their defect or deficiency.

5. Suggest reference at one location should be 1-3 literature. 

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

This paper proposed a recursive attentional convolutional neural network optimization algorithm to improve the accuracy of equipment fault detection and the anti-interference ability under bad weather. This reviewer has the following comments:

1.     While the author presents the Abstract, answer the questions carefully: What problem did you study and why is it important? What methods did you use? What were your main results? And what conclusions can you draw from your results? Please make your abstract with more specific and quantitative results while it suits broader audiences.

2.     The formats of the paper still need to be double checked and improved, such as the resolution in Figure 1, the axis label in Figure 6, and the number of equations.

3.     Particle Swarm Optimization (PSO) was used in the paper. Why did you choose PSO? Could other optimization methods be used here? A comparison with other methods would be better.

4.     Make sure the abbreviations in the paper are defined in detail. Make sure all variables in the paper are defined in detail as well.

5.     The simulation platform and programming languages adopted for the results are recommended to be explained in detail.

6.     The authors could identify potential flaws in the paper and possible directions for future research in the end.

Author Response

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Reviewer 3 Report

1) In Figure 1 , characters are too small. Please justify for easy readability.

2) Figure 3 is very important in this study. But, there is no explanation in the figure. Please add some important words in the figure.

 

Author Response

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Author Response File: Author Response.pdf

Reviewer 4 Report

This paper proposes an optimization algorithm based on recursive attention convolutional neural network to improve the detection accuracy of self-detonating insulators. Here are some comments:

1. The English writing really needs to be improved. It is hard for a English-native readers to understand the manuscript now.

2. In the introduction section:

a. a lot of background information needs reference. For example, "in addition, the occurrence of insulator faults is characterized by temporary and unpredictability, and the effective detection cannot be realized by manual alone."

b. what's your contribution? what's your motivation? what's your research objectives? 

3. A independent section about past research is very necessary

4. An independent section about methodology is necessary. Why you choose current technologies or methods? why it is better than the others? Please use a flow chart figure to display your methodologies?

5. Results should be put into an independent section

6.  A discussion section to discuss what the results mean? what are the limitations? is very necessary

 

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 4 Report

The authors have significantly addressed my comments