Health Assessment of Landing Gear Retraction/Extension Hydraulic System Based on Improved Risk Coefficient and FCE Model

Round 1

Reviewer 1 Report

The paper deals with an an improved fuzzy comprehensive evaluation model based on enhanced risk coefficient, however, is necessary to clarify some process used to perform this analysis. Also, some factual clarifications will be helpful as highlighted in the comments below. 

-The landing gear retraction and extension system is modeled as rigid body?

-How is included the stiffness of the components and its effect on the mechanical behaviour?

-In table II is expressed that at least the half of failures are related to the oil? How can reduced? Is necceary to include in the model oil characteristics?

-What are the main materials and how affect its mechanical behaviour?  (Please review the suggested references

-Figure 3, how affect the failure analysis the fatigue of the components?

-How is validated the proposal?.

-Based on conclusion (4), how can affect to change the parameters used for your model to only the parameters hydraulic oil and air, as well as valve sticking, or its effect is only at the moment of mixing it?

Please review the next papers and include it in your references.

 

- Fuzzy approach in modeling static and fatigue strength of composite materials and structures, Neurocomputing, Volume 393, 14 June 2020, Pages 156-164 https://doi.org/10.1016/j.neucom.2018.12.094

-Manufacturing effects on fatigue strength, Engineering Failure Analysis, Volume 108, January 2020, 104339 https://doi.org/10.1016/j.engfailanal.2019.104339

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

​​This study presents the health assessment method based on the fuzzy comprehensive evaluation for the landing gear operation. The landing gear system was appropriately characterized, and the evaluation indicators were well modeled by integrating practical manual data and simulation analyses. Nevertheless, some questionable points remain, and supplemental descriptions are required as follows.

1. Introduction: Check this research and add comparison with this study.
   • Chen, J., Chen, S., Liu, Z., Luo, C., Jing, Z., & Xu, Q. (2020). Health monitoring of landing gear retraction/extension system based on optimized fuzzy C-means algorithm. IEEE Access, 8, 219611-219621.
2. Line 41: Check and revise the full name of FMEA.
3. Figure 1: What is the meaning of “up only”?
4. Line 118: Descriptions about the operating sequences are not enough. Describe more about them. Otherwise, it is difficult to understand Figure 5.
5. Figure 2: Abbreviations MLG and NLG were used without explanation. Add the full names of them at least in the caption of Figure 2.
6. Line 182: Explain or define “λ” first.
7. Line 182: The sentence, “There is no direct connection between them.”, is not clear to understand. Does it mean the connection between “Frequency” and “λ” or between “Failure modes”?
8. Figures 5-10, 12, 14: Different types of lines or symbolic marks are required to distinguish the lines.
9. Section 4: Simulation results show very poor time resolutions, for example Figure 8 (b). How much time steps did authors use? The poor time step can also affect the parameters, γ and η as Eqs. (5) and (6). The poor resolution can especially underestimate the peak value than the actual value. Smaller time steps are required.
10. Line 235: What are the fundamentals for operating conditions? Add the references about “the standards for assessing the fault simulation”.
11. Line 269: If the readers are not familiar with AMESim, it is not easy to find which symbol means “filter”. Add some labels for important modules in Figure 4.
12. Line 269: Authors just mentioned “small-diameter” without any reference values and data. How did authors select the diameter of the valve to model the particle accumulation?
13. Tables 4-10: I would recommend authors to show the nominal (non-failure) conditions for each parameter in following figures.
14. Table 5: Are there special reasons for XX.1 values?
15. Table 6: Values 30 and -30 have to be changed.
16. Lines 377 and 385: How did authors model the indicators 9 and 10? The modeling methods for both are not clearly mentioned, however, the calculations for both were conducted in section 5.
17. Table 11: Explanation for Table 11 is not sufficient. Describe what those values mean in comparison.
18. Eqs. (7) – (12): Plots of the distributions are recommended to understand fuzzy levels.
19. Section 5: How did authors get Eq. (30)? Initial conditions for the example calculation have to be suggested first. Supplemental fuzzy level plot can be also suggested in the supplementary material.

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

 

 

The paper deals with an an improved fuzzy comprehensive evaluation model based on enhanced risk coefficient, however, is necessary to clarify some process used to perform this analysis. Also, some factual clarifications will be helpful as highlighted in the comments below. 

 

 

 

-What is the effect of Manufacturing process and how affect the durability? 

 

Suggested reference

 

-Manufacturing effects on fatigue strength, Engineering Failure Analysis, Volume 108, January 2020, 104339 https://doi.org/10.1016/j.engfailanal.2019.104339

 

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

The manuscript was well revised and all questions were appropriately answered.

This manuscript is acceptable to be published but be aware of the resolutions of figures.

The revised PDF version had very poor resolutions of important figures, e.g. Fig. 5 and more.

Authors have to keep the proper resolutions based on the instructions for authors provided by Applied Sciences.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf