Barkhausen Noise as a Reliable Tool for Sustainable Automotive Production

Round 1

Reviewer 1 Report

This work has presented some interesting idea to apply Barkhausen noise as a tool for automotive production. However, some aspects have to improve in order to publish it in the journal: 1. I don't see the comparison between static and dynamic measurements. 2. The interpretation of the results in the figures lacks details and discussion. 3. In which phase the microhardness is measured? What is the correlation between this parameter with which parameter of the Barkhausen noise signal? 4. Please, explain and interprete Figures 9 - 12, why you choose the angular dependence of the MBN in this case?

Author Response

Reviewer: I don't see the comparison between static and dynamic measurements.

Response: in order to clearly demonstrate the comparison, we altered appearance of Table 1.

Manuscript: we also added text as well as the new Figure 9.

Table 1 also indicates that MBN in the dynamic regime are remarkably lower as that obtained during the static regime due to the remarkable difference in frequency range of detected pulses. On the other hand, Table 1 also clearly proves that the higher MBN in the static regime directly correlates with the higher MBN values in dynamic regime and vice versa. FFT spectrum of the obtained MBN signals in the static regime illustrated in Figure 10 also demonstrates that the main difference between the static and dynamic MBN are due to the high frequency MBN pulses exceeding the threshold 200 kHz. Contribution of the low frequency MBN pulses is less pronounced and the electromagnetic pulses below 10 kHz represent mainly the mechanical vibrations filtered by the employed software [24, 25]. It is also worth to mention that the obtained number of MBN pulses (see Table 1) does not directly refers to the number of DWs in motion or their repetitive interaction with nitrides since DWs are clustered and their motion occurs in the form of avalanches [26, 27].

 

 

Reviewer: The interpretation of the results in the figures lacks details and discussion.

Response: we added further explanations and discussion

Manuscript:

Table 1 also indicates that MBN in the dynamic regime are remarkably lower as that obtained during the static regime due to the remarkable difference in frequency range of detected pulses. On the other hand, Table 1 also clearly proves that the higher MBN in the static regime directly correlates with the higher MBN values in dynamic regime and vice versa. FFT spectrum of the obtained MBN signals in the static regime illustrated in Figure 10 also demonstrates that the main difference between the static and dynamic MBN are due to the high frequency MBN pulses exceeding the threshold 200 kHz. Contribution of the low frequency MBN pulses is less pronounced and the electromagnetic pulses below 10 kHz represent mainly the mechanical vibrations filtered by the employed software [24, 25]. It is also worth to mention that the obtained number of MBN pulses (see Table 1) does not directly refers to the number of DWs in motion or their repetitive interaction with nitrides since DWs are clustered and their motion occurs in the form of avalanches [26, 27].

 

The lower temperature drops down the rate of diffusion of N in steel which in turn contributes to the lower density of nitrides [28] and higher MBN. Pinning strength of nitrides is very high since the nitrides are very fine and their size is close to the DWs thickness [29, 30]. It was also found that the thickness of the compound layer for the components emitting the higher MBN is more as compared with those emitting the lower MBN. This finding indicates that the contribution of the compound layer, as the region attenuating electromagnetic pulses towards the free surface [31], is only minor and the density of nitrides in the diffusion layer prevails. It should be considered that the lower temperatures decelerate diffusion of N to the deeper layers. For this reason, more free N can be found on the free surface which produces the thicker compound layer [6].

 

Reviewer: In which phase the microhardness is measured? What is the correlation between this parameter with which parameter of the Barkhausen noise signal?

Response: Due to very low thickness of compound layer the microhardness is measured in the diffusion layer only. The softer diffusion layer is linked with lower density of nitrides and the corresponding lower pinning strength of the matrix. This aspect contributes to longer free path of DWs motion, their earlier initiation which in turn contributes to the higher MBN.

Manuscript: we added this explanation

Due to very low thickness of the compound layer the microhardness is measured in the diffusion layer only. The softer diffusion layer is linked with the lower density of nitrides and the corresponding lower pinning strength of the matrix. This aspect contributes to the longer free path of DWs motion, their earlier initiation which in turn contributes to the higher MBN.

 

 

Reviewer: Please, explain and interprete Figures 9 - 12, why you choose the angular dependence of the MBN in this case?

Response: From our point of view it is clear especially with respect of Figure 2. Angular dependence is due to angular placement of samples in the chamber. Being so, we only keep the order of the samples in the chamber.

Manuscript: we added text and explanations

The angular dependence of MBN values is employed in order to follow the positioning of the samples in the chamber especially with respect of the position of the venting system, see also Figure 3.

 

The lower temperature drops down the rate of diffusion of N in steel which in turn contributes to the lower density of nitrides [28] and higher MBN. Pinning strength of nitrides is very high since the nitrides are very fine and their size is close to the DWs thickness [29, 30]. It was also found that the thickness of the compound layer for the components emitting the higher MBN is more as compared with those emitting the lower MBN. This finding indicates that the contribution of the compound layer, as the region attenuating electromagnetic pulses towards the free surface [31], is only minor and the density of nitrides in the diffusion layer prevails. It should be considered that the lower temperatures decelerate diffusion of N to the deeper layers. For this reason, more free N can be found on the free surface which produces the thicker compound layer [6].

Reviewer 2 Report

This article studied the non-destructive testing of components after plasma nitridation using Barkhausen noise technology for the sustainable production of components in the automotive industry. Here are my comments on this article:

 

1. References are scarce. For most sentences in the introduction, references should be provided as a basis for such a statement. Otherwise, it can only be judged as the subjective opinion of the authors. If your research is unique, please refer to the following papers that measure residual stress with Barkhausen noise.[ref.] doi.org/10.3390/ma14185374

http://doi.org/10.1063/1.4864963

 

2. Trends in related studies are needed. It is believed that you must have done research on relevant research trends before doing your research. Add something about it.

3. There is very little explanation of what kind of research you conducted. Draw a flow chart to visually describe the research you have done.

4. The description of the experiment is too scarce. Add a detailed description to live up to the chapter title 'Materials and Methods'.

5. I don't even know how to set up the experiment. Please explain what kind of equipment you used and attach a photo of the experimental setup, not only that of samples.

6. Be more specific about the title of Figure 5 & 8.

7. Conclusions are too subjective. I hope to close the article by adding a quantitative comment.

Author Response

Reviewer: References are scarce. For most sentences in the introduction, references should be provided as a basis for such a statement. Otherwise, it can only be judged as the subjective opinion of the authors. If your research is unique, please refer to the following papers that measure residual stress with Barkhausen noise.[ref.] doi.org/10.3390/ma14185374

http://doi.org/10.1063/1.4864963

Reviewer: Trends in related studies are needed. It is believed that you must have done research on relevant research trends before doing your research. Add something about it.

Response: we added the required references as well as additional ones in the introduction as well as in the chapter “Results of experiments”.

Manuscript: we added text and references

On the other hand, DWs alignment can be affected by stress state when tensile stresses align DWs towards the direction of the tensile stress whereas the compressive stresses align DWs perpendicularly against the direction of compressive stress [18, 19, 20].

 

18. Hwang, Y.; Kim, Y.; Seo, D.; Seo, M.; Lee, W.; Kim, K. Experimental Consideration of Conditions for Measuring Residual Stresses of Rails Using Magnetic Barkhausen Noise Method. 2021, 14, 5374; doi: 10.3390/ma14185374.
19. Cikalova, U.; Schreiber, J.; Hillman, S.; Meyendorf, N. Auto-calibration principles for two-dimensional residual stress measurements by Barkhausen noise technique, AIP Conference Proceedings 2014, 1581, 1243; doi: 10.1063/1.4864963.
20. Liu, J.; Tian, G.Y.; Gao, B.; Zeng, K.; Zheng, Y.; Chen, J. Micro-macro characteristics between domain wall motion and magnetic Barkhausen noise under tensile stress. Magn. Magn. Mater. 2020, 493, 165719; doi: 10.1016/j.jmmm.2019.165719.

 

24. MicroScan 600 Operating Instructions Manual V.5.4b 2015; Stresstech Group: Jyväskylä, Finland.
25. Blažek, D.; Neslušan, M.; Mičica, M.; Pištora, J. Extraction of Barkhausen noise from the measured raw signal in high-frequency regimes. 2016, 94, 456-463; doi: 10.1016/j.measurement.2016.08.022.
26. Bertotti, G.; Fiorillo, F. Bloch wall motion in Si-Fe investigated through surface e.m.f. measurements. Magn. Magn. Mater. 1984, 41, 303–305. https://doi.org/10.1016/0304-8853(84)90203-8.
27. Puppin, E. Statistical properties of Barkhausen noise in thin Fe films. Rev. Lett. 2000, 84, 5415; doi: 10.1103/PhysRevLett.84.4705.
28. Smallman, R.E.; Ngan, A. H.W. Modern Physical Metalugry, Butterworth-Heinemann, Amsterdam, 2014.
29. Dijkstra, L.J.; Wert, C. Effect of inclusions on coercive force of iron. Rev. 1950, 79, 979; doi: 10.1103/PhysRev.79.979.
30. Neslušan, M. et all. Barkhausen noise emission in Fe-resin soft magnetic composites, Magn. Magn. Mater. 2021, 525, 167683. doi: 10.1016/j.jmmm.2020.167683.

 

Reviewer: There is very little explanation of what kind of research you conducted. Draw a flow chart to visually describe the research you have done.

Reviewer: The description of the experiment is too scarce. Add a detailed description to live up to the chapter title 'Materials and Methods'.

Reviewer: I don't even know how to set up the experiment. Please explain what kind of equipment you used and attach a photo of the experimental setup, not only that of samples.

Response: Manuscript: we added further details as follows. Moreover, we also added the required flow chart and photos of devices employed in our study (Figure 2).

MBN refers to effective (rms) value of acquired Barkhausen noise signal. Apart from MBN, also the number of detected pulses, MBN envelopes and the corresponding PP values were analysed. PP refers to the position of the envelope in which this envelope attains the maximum.

Plasma nitriding process is running at the elevated temperatures without accelerated cooling rates. For this reason, it is considered that MBN in this particular case is mainly a function of microstructure and the height of surface irregularities. Microstructure is expressed in terms of the compound and diffusion layer thickness as well as microhardness profile of the diffusion layer. For these reasons, true interpretation of MBN signal is based on the aforementioned microstructure measurements (observations) as well as surface topography following the flowchart indicated in Figure 2.

To reveal the microstructure, 20 mm long pieces were routinely prepared for metallographic observations (hot moulded, ground, polished and etched by 3% Nital for 10 seconds). All measurements were carried out under laboratory conditions. Microstructure observations were carried using the light microscope Neophot 2 in software Niss Elements.

Microhardness (HV0.05) depth profiles were measured using an Innova Test 400TM (50 g for 10 s) on the cross-sectional cuts after metallographic observations. Presented microhardness were obtained averaging the five repetitive measurements.

                In order to analyse the contribution of surface height irregularities on MBN as a result of variable surface roughness also surface topography was studied using the laser confocal microscope Zeiss Axio applying the laser of wavelength 405 nm in ZEN software. The surface of the area 3 x 3 mm was scanned using the function Z-stack when the height of 20 mm was cut into 50 levels. Band pass filter according the ISO standard (band pass filter) was employed for data filtration and surface reconstruction. 

 

 

Reviewer: Be more specific about the title of Figure 5 & 8.

Response: we added specifications

Manuscript:

Figure 6. HV0.05 depth profiles in the positions emitting the different MBN.

Figure 9. MBN envelopes for the surface turned by the insert of low and high VB.

 

Reviewer: Conclusions are too subjective. I hope to close the article by adding a quantitative comment.

Response: added these comments

Manuscript:

The components emitting MBN about 250 mV (in the dynamic regime or in the frequency range of MBN pulses from 70 to 200 kHz) can be considered as acceptable. Increasing MBN (especially above 300 mV) indicates the decreased density of nitrides in the diffusion layer and the corresponding lower hardness. Also higher PP about 1 kA.m^-1 and the number of detected pulses about 35 0000 can be linked with adequate surface state whereas the decreasing number of MBN pulses and the lower PP indicate decreased matrix hardness.

Reviewer 3 Report

Reviewer comments on the paper “Barkhausen noise as a reliable tool for sustainable automotive production”

This paper the sustainable production of components in the automotive industry with the focus on non-destructive evaluation of components after plasma nitridation via Barkhausen noise technique.  The paper is very well organized and includes a novel material and method. The paper needs a revision before reconsideration. The reviewer comments are suggested as follows:

Although the title, materials and methods of the present paper are very interesting, however the main novelties of it are not clear for the reviewer. Authors are encouraged to add more comments on the novelties and main contributions of the present paper in Abstract and last paragraph of Introduction section.

What is application of the proposed method? Authors are suggested to provide some technical expressions on the application of the proposed method and needing to this new finding.

The Introduction section and the number of References is very limited and incomplete. Authors are suggested to add some references for improvement of Introduction such as: J Energy Storage, 2022, 49. doi: 10.1016/j.est.2022.104092; Comput-Aid Civil Infrast Eng, 2021, doi: 10.1111/mice.12684; Sustainability, 2021, 13(10), 5403. doi: 10.3390/su13105403; J Coastal Res, 2020, 103(sp1), 268-272; IEEE Trans Vehicular Techn, 2022, 71(1), 269-281. Fractal Fract 2021, 5(3), 119.

Authors are suggested to define all variables before first appearance in the text.

The discussion is not informative. It should be enriched with addition of some more important conclusions.

The results and discussion are very briefly organized. An extended result and discussion is required.

Author Response

Reviewer: Authors are encouraged to add more comments on the novelties and main contributions of the present paper in Abstract and last paragraph of Introduction section.

Response: we added further explanations

Manuscript:

last paragraph of introduction section as well as added in Abstract

Moreover, the study also unwraps the contribution of the diffusion and compound layers with respect of MBN and discusses the contribution of MBN pulses of the different frequency. Pinning strength of nitrides is indicated with respect of their size and the related thickness of DWs. Finally, this study clearly demonstrates how the MBN technique can be employed for the monitoring nitrided components and the corresponding optimisation of manufacturing cycles. 

 

Reviewer: What is application of the proposed method? Authors are suggested to provide some technical expressions on the application of the proposed method and needing to this new finding.

Response: we added explanations in Conclusions

Manuscript:

MBN can be easily adapted in automated cycles or in robotic cells. Therefore, the satisfactory precision of multiple and/or repetitive measurements and high sensitivity of monitoring process can be obtained. However, the critical threshold for approval or rejection of components should be validated during the preliminary phase in which surface state is linked with MBN and the extracted MBN features. The MBN technique can reveal risky factors in the automotive industry and the corresponding sustainability of manufacturing processes. High number of nitrided components can be measured within quite short time period but the finding as that presented in this study should be initially revealed.

 

 

Reviewer: The Introduction section and the number of References is very limited and incomplete. Authors are suggested to add some references for improvement of Introduction such as: J Energy Storage, 2022, 49. doi: 10.1016/j.est.2022.104092; Comput-Aid Civil Infrast Eng, 2021, doi: 10.1111/mice.12684; Sustainability, 2021, 13(10), 5403. doi: 10.3390/su13105403; J Coastal Res, 2020, 103(sp1), 268-272; IEEE Trans Vehicular Techn, 2022, 71(1), 269-281. Fractal Fract 2021, 5(3), 119.

Response: we added some of these references but some of proposed are quite out of the focus of this study

Manuscript: please check the manuscript as well as the list of references

18. Zhang, L.; Gao, T.; Cai, G.; Hai, K.L. Research on electric vehicle charging safety warning model based on back propagation neural network optimized by improved gray wolf algorithm. Energy Storage 2022, 49, 104092. doi: 10.1016/j.est.2022.104092.
19. Bie, Y.; Ji, J.; Wang, X.; Qu, X. Optimization of electric bus scheduling considering stochastic volatilities in trip travel time and energy consumption. Computer-aided civil infrastructure Eng. 2021, 36, 1530-1548. doi: 10.1111/mice.12684.
20. Wang, G.; Zhang, Y. Dynamic Simulation Analysis of Port Economic Throughput Difference in Marine Environment. Coastal Res. 2020, 103, 268-272. doi: 10.2112/SI103-057.1.

 

 

Reviewer: Authors are suggested to define all variables before first appearance in the text.

Response: we have found that we need to introduce parameter PP.

Manuscript: we added text

MBN refers to effective (rms) value of acquired Barkhausen noise signal. Apart from MBN, also the number of detected pulses, MBN envelopes and the corresponding PP values were analysed. PP refers to the position of the envelope in which this envelope attains the maximum.

 

Reviewer: The discussion is not informative. It should be enriched with addition of some more important conclusions.

Reviewer: The results and discussion are very briefly organized. An extended result and discussion is required.

Response: we added further explanations and discussion. We added also new figure

Manuscript:

Table 1 also indicates that MBN in the dynamic regime are remarkably lower as that obtained during the static regime due to the remarkable difference in frequency range of detected pulses. On the other hand, Table 1 also clearly proves that the higher MBN in the static regime directly correlates with the higher MBN values in dynamic regime and vice versa. FFT spectrum of the obtained MBN signals in the static regime illustrated in Figure 10 also demonstrates that the main difference between the static and dynamic MBN are due to the high frequency MBN pulses exceeding the threshold 200 kHz. Contribution of the low frequency MBN pulses is less pronounced and the electromagnetic pulses below 10 kHz represent mainly the mechanical vibrations filtered by the employed software [24, 25]. It is also worth to mention that the obtained number of MBN pulses (see Table 1) does not directly refers to the number of DWs in motion or their repetitive interaction with nitrides since DWs are clustered and their motion occurs in the form of avalanches [26, 27].

 

The lower temperature drops down the rate of diffusion of N in steel which in turn contributes to the lower density of nitrides [28] and higher MBN. Pinning strength of nitrides is very high since the nitrides are very fine and their size is close to the DWs thickness [29, 30]. It was also found that the thickness of the compound layer for the components emitting the higher MBN is more as compared with those emitting the lower MBN. This finding indicates that the contribution of the compound layer, as the region attenuating electromagnetic pulses towards the free surface [31], is only minor and the density of nitrides in the diffusion layer prevails. It should be considered that the lower temperatures decelerate diffusion of N to the deeper layers. For this reason, more free N can be found on the free surface which produces the thicker compound layer [6].

Round 2

Reviewer 1 Report

Accept!!

Reviewer 2 Report

I was surprised at how quickly the revision was submitted while making various comments. All points to be pointed out have been thoroughly corrected, and therefore there is no further request for correction.

Reviewer 3 Report

The revised paper is suggested for publication.