A Novel Method for Early Fatigue Damage Diagnosis in 316L Stainless Steel Formed by Selective Laser Melting Technology
Abstract
:1. Introduction
2. Theoretical Model of Acoustic Nonlinearity Caused by Early Fatigue Damage
3. Experimental Procedures
3.1. Material and Specimen Preparation
3.2. Experimental Setup and Data Collection Method
4. Method for Fatigue Damage Diagnosis in 316L Stainless Specimen
4.1. Fast Fourier Transform (FFT)
4.2. EMD-ESI-FFT
4.2.1. Empirical Mode Decomposition (EMD)
- Throughout the data segment, the result of subtracting the number of extreme points and zero crossings of the signal is less than or equal to 1.
- At any point on the time axis, the mean value of the upper and lower envelopes fitted by the maximum and minimum points is zero. That is, the upper and lower envelopes are locally symmetrical with the time axis as the axis of symmetry.
- The maximum points in x(n) are screened out, and cubic spline interpolation is performed on them to fit the upper envelope of xmax(n). Similarly, the lower envelope xmin(n) of x(n) can be obtained. The mean value of the upper and lower envelope is obtained at each time point:
- 2.
- Subtract the amplitude of m(n) from the original signal x(n) to obtain a new signal h(n):h(n) = x(n) − m(n)
- 3.
- If h(n) does not meet the IMF requirements, x(n) = h(n), and continue the steps (1) and (2). When h(n) meets the requirements, c1(n) = h(n), and extract c1(n) from x(n):r1(n) = x(n) − c1(n)
- 4.
- Repeat steps (1) and (2) for signal r1(n) to obtain c2(n). By analogy, continue to repeat steps (1) and (2) to obtain all the components that meet the IMF requirements.
- 5.
- When the residual component rL(n) becomes a monotonic function sequence or a constant series, the loop ends and the EMD is completed. The original signal x(n) is decomposed into a series of steady-state signals c1(n), c2(n), c3(n), …, cL(n) and a residual component rL(n); the residual component rL(n) represents the overall change trend of the signal.
4.2.2. Extract the Specific IMF and Obtain the Fatigue Damage Information
4.3. Results and Discussion
4.3.1. Comparison of FFT and EMD-ESI-FFT
4.3.2. Transmission Electron Microscope (TEM) Experimental Results
5. Conclusions
- Eliminating interference signals and extracting effective information characterizing material damage are key techniques for nonlinear ultrasonic testing. The EMD-ESI-FFT method for fatigue damage diagnosis was proposed in this paper. In the process of nonlinear ultrasonic testing, the nonlinear acoustic effect caused by fatigue damage has the characteristics of localization, and the distortion process time is relatively short. EMD-ESI-FFT can filter out the redundant interference signals in the original signal, which is more conducive to analyzing the nonlinear distortion process and evaluating the damage degree of materials.
- According to the principle of higher harmonic generation, the fatigue damage information is usually extracted by the classical FFT method. The ultrasonic signals have nonlinear and unsteady characteristics; FFT signal processing technology cannot effectively filter the interference signals in the ultrasonic signal. Theoretical analysis reveals that EMD is the process of transforming unsteady signals into steady signals. The unsteady signal can be regarded as a combination of multiple IMFs. Extracting the instantaneous frequency of a single IMF can characterize the characteristics of each frequency band in the unsteady signal due to fatigue damage information only existing in a specific IMF. The method to extract the specific IMF is described in this paper. Experimental results indicate that compared with FFT, the EMD-ESI-FFT method is more sensitive in identifying the early damage in SLM 316L stainless parts induced by fatigue loading, which is equivalent to improving the early fatigue micro-damage identification and diagnosis ability and can better ensure the service safety of important metal parts.
- According to the theoretical model of acoustic nonlinearity caused by early fatigue damage, the results of nonlinear ultrasonic testing agree well with TEM experimental analysis and the theoretical model of acoustic nonlinearity caused by dislocations. Therefore, the change in β/β0 reflects the generation and evolution of dislocation structure during the low-cycle fatigue regime of the SLM 316L stainless steel specimen and reveals the early fatigue damage mechanism of this metal part.
- The future development direction is the combination of nonlinear ultrasonic testing technology with big data and cloud computing to realize the full-time structural health monitoring of important components. Through the fusion analysis and data mining of historical data, the remaining life of components and materials can be predicted and the safety and reliability of important components in service can be improved.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Chemical Composition | Cr | C | Mo | Ni | Mn | Si | P | O | Fe |
---|---|---|---|---|---|---|---|---|---|
Mass Fraction (%) | 17.6 | 0.04 | 2.05 | 12.05 | 0.3 | 0.85 | 0.04 | <0.1 | Bal. |
Scanning Speed (mm/s) | Laser Power (W) | Layer Thickness (μm) | Scanning Interval (μm) | Spot Diameter (μm) | Volume Fraction of Oxygen (%) |
---|---|---|---|---|---|
780 | 260 | 25 | 70 | 85 | ≤0.03 |
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Yan, X.; Tang, X. A Novel Method for Early Fatigue Damage Diagnosis in 316L Stainless Steel Formed by Selective Laser Melting Technology. Materials 2023, 16, 3363. https://doi.org/10.3390/ma16093363
Yan X, Tang X. A Novel Method for Early Fatigue Damage Diagnosis in 316L Stainless Steel Formed by Selective Laser Melting Technology. Materials. 2023; 16(9):3363. https://doi.org/10.3390/ma16093363
Chicago/Turabian StyleYan, Xiaoling, and Xiujian Tang. 2023. "A Novel Method for Early Fatigue Damage Diagnosis in 316L Stainless Steel Formed by Selective Laser Melting Technology" Materials 16, no. 9: 3363. https://doi.org/10.3390/ma16093363