Case Depth Prediction of Nitrided Samples with Barkhausen Noise Measurement
Abstract
:1. Introduction
2. Materials and Methods
2.1. Material Description
2.2. Sample Preparation
2.3. Measurement Devices
2.4. Measurements and Data Pre-Processing
2.5. Modelling Approach
- Identification of the full model (all features and their two-variable interactions);
- Detection of outliers;
- Elimination of excess terms from the model;
- Identification of the model with the appropriate terms excluding the detected outliers;
- Evaluation of the model performance and structure.
3. Results
3.1. Modelling of Hardness
3.1.1. Non-Ground Samples with Compound Layer
3.1.2. Ground Samples
3.2. Modelling of Case Depths
3.2.1. Non-Ground Samples with Compound Layer
3.2.2. Ground Samples
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Series Name | Material | Samples * | Threshold Values for Case Depth (HV) |
---|---|---|---|
A | GKP | A12, A40, A80, A160 | 550 |
B | S132 | B12, B40, B80, B160 | 520 |
C | En19 | C12, C40, C80, C160 | 400 |
U | En40B | U12, U40, U80, U160 | 400 |
Material | C (wt%) | Cr (wt%) | Mo (wt%) | V (wt%) | Mn (wt%) | Si (wt%) | P (wt%) | S (wt%) |
---|---|---|---|---|---|---|---|---|
GKP (32CrMoV5) | 0.3 | 1.4 | 1.2 | 0.3 | ||||
BS132 | 0.35–0.43 | 3.0–3.5 | 0.8–1.2 | 0.15–0.25 | 0.4–0.7 | 0.1–0.35 | 0.02 | 0.02 |
En19 (709M40) | 0.36–0.44 | 0.9–1.2 | 0.25–0.35 | 0.7–1.0 | 0.1–0.35 | 0.035 | 0.04 | |
En40B (722M24) | 0.2–0.28 | 3.0–3.5 | 0.45–0.65 | 0.45–0.7 | 0.1–0.35 | 0.035–0.04 |
Nitriding Time (h) | A (GKP) | B (S132) | C (En19) | U (En40B) |
---|---|---|---|---|
12 | 0.34 | 0.18 | 0.09 | 0.15 |
40 | 0.38 | 0.29 | 0.15 | 0.25 |
80 | 0.52 | 0.44 | 0.24 | 0.35 |
160 | 0.84 | 0.56 | 0.24 | 0.45 |
Term | Coefficient | Standard Error | p-Value | Contribution (%) |
---|---|---|---|---|
xrms | a1 = −6.70 | 0.76 | 1.28 × 10−6 | 45.5 |
xrmsxp | a12 = 0.54 | 0.054 | 3.35 × 10−7 | 54.5 |
Term | Coefficient | Standard Error | p-Value | Contribution (%) |
---|---|---|---|---|
xrms | a1 = −5.14 | 0.50 | 2.47 × 10−7 | 41.4 |
xrmsxp | a12 = 0.42 | 0.036 | 6.27 × 10−8 | 58.6 |
Term | Coefficient | Standard Error | p-Value | Contribution (%) |
---|---|---|---|---|
xHV | b1 = 0.0012 | 0.00022 | 0.00015 | 49.4 |
xSD | b2 = −0.54 | 0.12 | 0.00068 | 50.6 |
Term | Coefficient | Standard Error | p-Value | Contribution (%) |
---|---|---|---|---|
xHV | b1 = 0.0052 | 0.00076 | 1.64 × 10−6 | 49.0 |
xSD | b2 = −2.36 | 0.42 | 0.00012 | 51.0 |
Term | Coefficient | Standard Error | p-Value | Contribution (%) |
---|---|---|---|---|
xHV | b1 = −0.0017 | 0.00036 | 0.00056 | 11.1 |
xSD | b2 = −0.69 | 0.093 | 1.31 × 10−5 | 47.1 |
xHVxSD | b12 = 0.0010 | 0.00012 | 4.43 × 10−6 | 41.8 |
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Sorsa, A.; Santa-aho, S.; Aylott, C.; Shaw, B.A.; Vippola, M.; Leiviskä, K. Case Depth Prediction of Nitrided Samples with Barkhausen Noise Measurement. Metals 2019, 9, 325. https://doi.org/10.3390/met9030325
Sorsa A, Santa-aho S, Aylott C, Shaw BA, Vippola M, Leiviskä K. Case Depth Prediction of Nitrided Samples with Barkhausen Noise Measurement. Metals. 2019; 9(3):325. https://doi.org/10.3390/met9030325
Chicago/Turabian StyleSorsa, Aki, Suvi Santa-aho, Christopher Aylott, Brian A. Shaw, Minnamari Vippola, and Kauko Leiviskä. 2019. "Case Depth Prediction of Nitrided Samples with Barkhausen Noise Measurement" Metals 9, no. 3: 325. https://doi.org/10.3390/met9030325