Coal Combustion Warning System Based on TDLAS and Performance Research

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Please see the attached pdf file.

Comments for author File: Comments.pdf

Author Response

Thank you for pointing out the shortcomings of the article. We have made targeted modifications and will respond to each of your suggestions one by one.

Comments 1: The writing of the manuscript should be improved, not only the grammar or typos, but the statements and expressions of ideas should be revised. For example, in the abstract, the keywords of coal safety, monitoring should appear to emphasize the background and show what this work is about more clearly. The two sentences of “Through the temperature compensation algorithm and normalized signals, the impact of factors such as ambient temperature and environmental noise is reduced, effectively improving the signal-to-noise ratio and accuracy. The impact of external factors was mitigated by the temperature compensation algorithm and signal normalization. ”are talking about the same idea, so that the information conveyed by the abstract is reduced. The author should show their methods, results, and scientific or practical conclusions in the abstract briefly and clearly. In the introduction, “Although they are cost-effective, they are unable to achieve the detection sensitivity required to prevent coal smoldering due to the limitations of their detection principle.” “Similarly, they have a limited detection limit and are more sensitive to the environment, which means they are susceptible to interference from other gases.” Please present the required precision and limitations. It is unnecessary to spend a paragraph to point out the disadvantages of other methods to highlight the advantages of TDLAS. No method is perfect for general detection purpose. The authors should show the key points in the telemetry of coal safety which only TDLAS satisfies. “Dong Lei, Ma Weiguang and Yin Wangbao from Shanxi University conducted the harmonic detection of methane gas using a digital lock-in amplifier”, only the first author should be listed in the citation.

Response 1: The current version of this paper still has several rough edges, and we sincerely appreciate the reviewers' insightful suggestions. Below is a summary of the revisions made:

1. The abstract has been revised to place greater emphasis on keywords such as "coal safety" and "monitoring," with some sections rewritten for clarity.
2. Redundant expressions have been removed to make the paper more concise.
3. The introduction has been expanded to include specific quantitative performance metrics for existing catalytic combustion methane sensors, an overview of electrochemical methane sensors, and additional research on methane remote sensing. We acknowledge that our initial literature review was insufficient in these areas and sincerely apologize for the oversight.
4. Descriptions of other sensor types have been streamlined, while discussions on TDLAS and coal safety have been expanded to better align with the paper's main focus.
5. We sincerely apologize for our lack of prior submission experience and appreciate the guidance on proper citation practices. The citations have now been corrected in accordance with academic standards.

 

Comments 2: In the introduction part, there are only three references for the TDLAS detection of coal smoldering, which is insufficient to show the advances in the field, nor the problems to be solved are clearly pointed out and summarized. The motivations of the present work need to be emphasized.

Response 2: Indeed, there are many outstanding studies and recent advancements in the field of methane remote sensing. While they may not specifically target the monitoring of coal smoldering, they can still be applied to coal safety to achieve effective smoldering detection. We greatly appreciate your suggestion.

Currently, TDLAS has seen limited application in coal smoldering monitoring. Generally, due to the high methane concentrations in natural gas leaks and coal mine environments, TDLAS is more common in this area. In coal spontaneous combustion early warning systems, point-type methane sensors are more commonly used, but they cannot measure methane concentrations along a straight path. The development trend in methane remote sensing focuses on higher precision and smaller device sizes. However, there remain significant challenges in remote sensing of low-concentration methane. Detecting low levels of methane requires high-precision instrumentation and strong resistance to environmental interference

To align with this trend and solve these problems, we have incorporated the latest research progress from scholars such as Yang Haoqing and Wu Qi in methane remote sensing. This addition helps readers better understand the purpose and significance of this paper.

 

Comments 3: For the line selection part, a graph of gaseous emissions for different stages of coal combustion would be very helpful to clarify the selection without too much words.

Response 3: You raise an excellent point. Incorporating gas emission profiles from different stages of coal combustion would indeed make the paper more intuitive. We have offered the new graph to show the gaseous emissions for different stages of coal combustion. However, it's important to note that gas emissions vary significantly depending on coal types and environmental conditions. While there are numerous studies on gas emissions from coal combustion in power plants, research focusing on gas emissions during coal storage smoldering is scarce.

Clearly, there are differences between gas emissions from active coal combustion and smoldering, meaning combustion data can only serve as a reference. This highlights the significance and novelty of our study, which directly measures gas emissions through controlled coal smoldering experiments. Due to limitations in equipment and resources, we focused specifically on methane concentration measurements during smoldering.

In the revised manuscript, we've included reference data on early-stage gas emissions from coal combustion for context. For future research, we aim to expand our investigations to measure other gas species emitted during coal smoldering. This would provide a more comprehensive understanding of the smoldering process and further contribute to coal safety monitoring.

 

Comments 4: The structure of the gas cavity, the position of the diffuse reflecting plate and how the absorption information is collected should be provided in Section 4.1.

Response 4: Thank you for your suggestion. Figure 5 has now been revised to better illustrate the structural details.

 

Comments 5: Typical raw signals and processed ones should be provided.

Response 5: Thank you for pointing this out. Indeed, this was an oversight on my part. In the revised version, we have supplemented Figure 6(a) and (d) with the original data plot.

 

Comments 6：Please specify how to obtain Equation 16.

Response 6: Thank you for your valuable feedback. We acknowledge that presenting Equation 16 directly was indeed abrupt. In the revised version, we have：

1. Added a detailed derivation process in Section 4.2
2. Highlighted the key steps in red font for better visibility
3. Structured the derivation logically to enhance readability

These modifications will help readers clearly follow the mathematical development and understand the theoretical foundation.

 

Comments 7：The title of Section 5.1 is improper.

Response 7: Thank you for your suggestion. The section heading has now been revised to: "Performance of the Instrument". The new title more accurately represents the section's emphasis on system capabilities and measurement results

 

Comments 8：The 2f/1f signal method is well-established in WMS. Why do the authors reexamine its validity in Figure 6?

Response 8: You make an excellent point about the practical engineering considerations in signal processing. While this discussion may appear overly detailed, it reflects an important real-world trade-off we encountered. In specific engineering practice, 2f/1f signaling is not always the best solution, and sometimes there may be little or even no performance gain. The literature shows divergent approaches - Zhang Keke's team successfully used 1f signals (Zhang Keke, Qi Yong, Fu Xiao, et al. Research on methane concentration detection system based on TDLAS first harmonic and its temperature compensation [J]. Shandong Science, 2014, 27(01): 16-21+44.) while Li P.'s group achieved results with 2f peaks (Li, P.; Lin, G.; Chen, J.; Wang, J. Off-Axis Integral Cavity Carbon Dioxide Gas Sensor Based on Machine-Learning-Based Optimization. Sensors 2024, 24, 5226. https://doi.org/10.3390/s24165226), which demonstrates there's no universal best solution. In our testing, we found that while 2f/1f normalization theoretically offers advantages, its practical implementation introduced computational overhead that sometimes-caused system freezes. These engineering realities explain why we carefully evaluated both approaches despite the theoretical preference for 2f/1f.

In our modified manuscript, we've highlighted these practical considerations in red to help readers understand why this seemingly technical detail actually has important implications for real-world deployment. Our testing ultimately showed 2f/1f provided sufficient performance benefits in our specific setup to justify its use, but this might not hold true for all applications.

 

Comments 9：Are there any applications to practical scenarios for coal combustion monitoring? Since there is nothing new in the method, the authors must clarify their applications to coal combustion monitoring with sufficient novelty in overcoming the problems related to the detection of coal volatiles.

Response 9:

You raise a critically important point regarding the technological context. Currently, TDLAS technology, utilizing techniques such as multi-pass cells and integrated cavities, has been applied in monitoring coal combustion and other areas. Its characteristics include ultra-high precision (capable of reaching ppb levels) and single-point measurement. However, these two features are of limited use in detecting coal smoldering, as ppt-level precision is unnecessary for such detection, and the point-based measurement also restricts its monitoring range. The key innovation in our work lies in the remote scanning configuration that enables path-integrated methane concentration measurements across coal piles

Thank you for prompting us to clarify this distinction. Part of the article has been rewritten to better articulate the practical significance in coal safety. The revised version more accurately positions our contribution as an innovative application of established technology to solve an unmet industrial need.

 

Comments 10：The conclusion part should be improved to emphasize the novelty and findings for the present work.

Response 10: We have carefully revised the conclusion section to better highlight the novel aspects and key findings of our study. The conclusions now more clearly articulate how our work advances the field beyond existing TDLAS applications

 

Comments 11：The text in Figures 1,5,6, 8, 10 are too small for reading. Please improve the figures using Times New Roman font or Arial font.

Response 11: The text in the image has now been enlarged and the font has been changed to Times New Roman. hopefully the image now meets your requirements.

 

Comments 12：Section 2.2, Beer-Labert Law should be Beer-Lambert Law

Response 12: Thank you for being able to point out the error. The error has now been corrected.

 

Reviewer 2 Report

Comments and Suggestions for Authors

This paper presents a remote methane detection device designed for coal smoldering early warning. Field experiments were conducted to quantify the instrument's performance metrics, while simulated experiments validated the effectiveness of the temperature drift control algorithm. However, several critical issues require resolution prior to publication:

1. The numerical expression "109" in lines 24-25 should be corrected to scientific notation (10⁹).
2. The comparative analysis of traditional methane sensors requires enhancement through quantitative performance metrics (e.g., detection limits/accuracy specifications).
3. The thermal management strategy described in lines 360-363 (fan-cooled enclosure) represents standard engineering practice and could be streamlined.
4. The observed laboratory temperature-induced reading drift would benefit from graphical illustration showing temporal temperature fluctuations and corresponding measurement deviations.
5. The concluding statement regarding optimal working distance (17m) and maximum operational range (≤40m) appears inconsistent with the technical discussion in lines 419-429. This discrepancy necessitates clarification through textual revision.

 

Author Response

Thank you for pointing out the shortcomings of the article. We have made targeted modifications and will respond to each of your suggestions one by one.

Comment 1: The numerical expression "109" in lines 24-25 should be corrected to scientific notation (10⁹).

Response 1: Thank you for your valuable feedback. We have now corrected both errors in the manuscript and highlighted the revisions in red for easy identification.

 

Comment 2: The comparative analysis of traditional methane sensors requires enhancement through quantitative performance metrics (e.g., detection limits/accuracy specifications).

Response 2: Indeed, specific performance metrics are more indicative of the accuracy of the comparison. Now the performance indexes of traditional methane sensors are explained in the paper, and some references are added for comparison. Now the comparison between traditional methane sensors and optical methane sensors is more obvious.

 

Comment 3: The thermal management strategy described in lines 360-363 (fan-cooled enclosure) represents standard engineering practice and could be streamlined.

Response 3: Thank you for your suggestion. We have revised the manuscript by removing the fan cooling-related content, resulting in a more streamlined presentation.

 

Comment 4: The observed laboratory temperature-induced reading drift would benefit from graphical illustration showing temporal temperature fluctuations and corresponding measurement deviations.

Response 4: Thank you for your suggestion. We have supplemented the manuscript with detailed temperature monitoring data collected in the laboratory environment in figure 9. 

 

Comment 5: The concluding statement regarding optimal working distance (17m) and maximum operational range (≤40m) appears inconsistent with the technical discussion in lines 419-429. This discrepancy necessitates clarification through textual revision.

Response 5: There was an error here, namely that at 40 metres it is no longer possible to achieve a negative burn warning for coal. This has been corrected in the summary section of the revised version. Thank you for your correction.

Reviewer 3 Report

Comments and Suggestions for Authors

The paper describes a remote sensing system for coal combustion early warning. A methane detection prototype has been devised and implemented to preliminary testing. The temperature correction algorithm represents innovative advancements. However, the article exhibits several shortcomings, and it is recommended for acceptance contingent upon revisions.

 

1The manuscript insufficiently elucidates the theoretical framework governing ambient temperature-induced fluctuations in methane absorption intensity. Specifically, the analysis lacks rigorous quantitative characterization of the expected variation range (e.g., temperature coefficient).

 

2Further additions are needed. The article contains inaccuracies in certain parameter descriptions. For instance, the methane absorption peak is actually measured at 1653.7 nm, whereas the article states it as 1653 nm. Please make the necessary corrections.

 

3The experimental section lacks important details such as coal type, wind speed, etc. Further additions are needed.

 

4The current description of the fiber optic attenuator's role in emulating telemetry distance remains superficial. A rigorous mathematical treatment is required, explicitly demonstrating how optical power attenuation (dB scale) maps to equivalent transmission distances via the relation

 

5An inconsistency exists in figure designation: the spectral comparison plot labeled as "Figure 2" corresponds to the "Figure 3".

 

6English can be improved.

 

7Please include the most recent publications about gas sensing and TDLAS technology such as [Opto-Electron. Adv. 7.3 (2024): 230230], [Light: Science & Applications 13.1 (2024): 77], [Photoacoustics 33 (2023): 100559].

Author Response

Thank you for pointing out the shortcomings of the article. We have made targeted modifications and will respond to each of your suggestions one by one.

Comments 1: The manuscript insufficiently elucidates the theoretical framework governing ambient temperature-induced fluctuations in methane absorption intensity. Specifically, the analysis lacks rigorous quantitative characterization of the expected variation range (e.g., temperature coefficient).

Response 1: Thank you for pointing out this issue. In the revised manuscript, we have added graphs showing the variation of methane absorption capacity at different temperatures from the HITRAN database and conducted corresponding analyses. The results demonstrate that the theoretical variation range is generally consistent with actual observations.

 

Comments 2: Further additions are needed. The article contains inaccuracies in certain parameter descriptions. For instance, the methane absorption peak is actually measured at 1653.7 nm, whereas the article states it as 1653 nm. Please make the necessary corrections.

Response 2: You have read the content with great attention to detail. The discrepancy arose because there was a slight difference between the position of the methane absorption peak and the laser's specified parameters (the methane absorption peak occurs at 1653.7 nm, whereas the laser's rated parameter is 1653 nm). This inconsistency led to the error in question. The error has now been corrected in the article.

 

Comments 3: The experimental section lacks important details such as coal type, wind speed, etc. Further additions are needed.

Response 3: Thank you very much for your insightful suggestions. Regarding the aforementioned details, I've already added supplementary text in the document to clarify and address them appropriately.

 

Comments 4: The current description of the fiber optic attenuator's role in emulating telemetry distance remains superficial. A rigorous mathematical treatment is required, explicitly demonstrating how optical power attenuation (dB scale) maps to equivalent transmission distances via the relation

Response 4: The sudden presentation of distances in the article did indeed come across as abrupt. Meanwhile, during the revision process, an error was identified where 30 meters was mistakenly written as 40 meters. I sincerely apologize for this oversight. In the revised manuscript, the calculation process for the distance in question has been thoroughly laid out, with the hope of fostering clearer comprehension among readers.

 

Comments 5: An inconsistency exists in figure designation: the spectral comparison plot labeled as "Figure 2" corresponds to the "Figure 3".

Response 5: This was indeed a careless mistake, and I truly appreciate you pointing it out.

 

Comments 6: English can be improved.

Response 6: I am very sorry for the bad reading experience. Some of the statements in the article have been touched up and rewritten, and we hope that you will be satisfied with this improvement.

 

Comments 7: Please include the most recent publications about gas sensing and TDLAS technology such as [Opto-Electron. Adv. 7.3 (2024): 230230], [Light: Science & Applications 13.1 (2024): 77], [Photoacoustics 33 (2023): 100559].

Response 7: Thank you for your suggestion. We have updated the references in the manuscript by adding several recent studies relevant to this research field. Supplementary references are highlighted in red and I hope it will meet your requirements.

Reviewer 4 Report

Comments and Suggestions for Authors

Overall, the manuscript is in high-quaility and would like to address just a few minor revisions to be completed. 

1) in 5.4 Stability difference under different signal strength section, the time window for stability measurement need to increase from 300 seconds to 1000 seconds for demonstrating its long-term measurement capability.

2) In Fig 9. it looks a bit odd that the slope of allan variance do not satisfy tau^(-0.5) trend before reaching its local minium point. (Tau-averaging time.) Please justify this trend. 

Author Response

Thank you for pointing out the shortcomings of the article. We have made targeted modifications and will respond to each of your suggestions one by one.

Comments 1: Stability difference under different signal strength section, the time window for stability measurement need to increase from 300 seconds to 1000 seconds for demonstrating its long-term measurement capability.

Response 1: Your suggestion is highly valuable. Indeed, the instrument's testing performance showed certain variations as time varies. We have retested the equipment and replaced Figure 13 accordingly. Under these conditions, the standard deviation of the readings exhibited some degree of increase. Testing over longer durations does better reflect the device's stability, and we sincerely appreciate your insightful recommendation.

 

Comments 2: In Fig 9. it looks a bit odd that the slope of allan variance do not satisfy tau^(-0.5) trend before reaching its local minium point. (Tau-averaging time.) Please justify this trend.

Response 2: Your query is very valuable. While these data may appear unusual at first glance, such phenomena are actually quite common in practical sensor testing. Within the τ range of 2 seconds to approximately 30 seconds, the Allan deviation slope does not exhibit the expected τ^(−0.5) trend. As Allan deviation serves as an important tool for analyzing frequency stability in clocks or oscillators, different noise types can lead to distinct trend characteristics in its plot. The τ interval between 2 and 30 seconds can be considered a short-term range, where short-term noise - particularly flicker noise - may dominate. We speculate that the observed deviation could be attributed to significant flicker noise present in the testing environment, potentially originating from either the laser source or other electronic components. We sincerely appreciate your question regarding this matter, and a detailed explanation has been incorporated into the manuscript to facilitate readers' understanding.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors have sufficiently addressed the concerns raised by the reviewer. The manuscript can be accepted after the quality of the figures are further improved with high resolution and uniform standards in font style and visual size.

Reviewer 2 Report

Comments and Suggestions for Authors

This work  has been well done.