Preprocessing Acoustic Emission Signal of Broken Wires in Bridge Cables
Abstract
:1. Introduction
2. Materials and Methods
2.1. Basic Theory of Acoustic Emission Technology
2.1.1. Generation and Propagation of Acoustic Emission Signals
2.1.2. Waveform and Parameters of Acoustic Emission Signal
2.1.3. Acoustic Emission Signal Analysis Methods
2.2. Acoustic Emission Signal Segmentation Algorithm
- Threshold (Thr):
- Hit Definition Time (HDT):
- Hit Lockout Time (HLT):
- Maximum Duration (MD):
2.3. Noise Signal Acquisition Experiment
3. Results
3.1. Segmentation Algorithm Results
3.2. Feature Parameter Extraction
3.3. Comprehensive Noise Analysis
3.3.1. Time Domain Analysis
- Impact-amplitude correlation analysis;
- 2.
- Ringing count-duration correlation analysis;
- 3.
- Amplitude-energy correlation analysis;
- 4.
- Impact-vehicle count correlation analysis;
3.3.2. Frequency Domain Analysis
- Signal spectrum analysis
- 2.
- Energy-average frequency correlation analysis
- 3.
- ASL-centroid frequency correlation analysis
3.3.3. Wavelet Time-Frequency Analysis
4. Conclusions
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Serial Number | Rise Time (µs) | Duration (µs) | Ringing Count | Amplitude (dB) | Energy (ms*mV) | AF (kHz) | ASL dB |
---|---|---|---|---|---|---|---|
1 | 11,949 | 12,396 | 13 | 53 | 2.86 | 1.05 | 28 |
2 | 199 | 42,193 | 375 | 61 | 76.53 | 9.68 | 24 |
3 | 3977 | 46,368 | 449 | 62 | 90.60 | 10.87 | 25 |
4 | 1442 | 50,859 | 553 | 58 | 59.76 | 8.58 | 22 |
5 | 1425 | 46,252 | 397 | 59 | 58.15 | 8.02 | 23 |
6 | 628 | 44,164 | 354 | 60 | 62.19 | 13.58 | 24 |
7 | 151 | 38,947 | 529 | 62 | 91.63 | 12.43 | 26 |
8 | 3514 | 48,656 | 605 | 62 | 91.85 | 14.43 | 26 |
9 | 5220 | 44,630 | 644 | 60 | 100.40 | 12.75 | 26 |
10 | 1228 | 48,475 | 618 | 61 | 76.53 | 15.64 | 26 |
11 | 4376 | 13,906 | 42 | 54 | 11.91 | 3.02 | 19 |
…… | |||||||
90 | 967 | 17,304 | 222 | 53 | 23.01 | 13.59 | 39 |
91 | 633 | 834 | 20 | 49 | 27.49 | 15.92 | 27 |
92 | 4070 | 27,566 | 122 | 53 | 23.74 | 4.43 | 19 |
93 | 12,087 | 38,825 | 436 | 56 | 53.22 | 11.23 | 23 |
94 | 34 | 4632 | 33 | 52 | 4.97 | 7.12 | 21 |
95 | 2051 | 16,362 | 321 | 58 | 30.35 | 19.62 | 25 |
96 | 1537 | 12,592 | 171 | 58 | 22.20 | 13.58 | 25 |
97 | 2147 | 9154 | 85 | 53 | 10.77 | 9.29 | 22 |
98 | 4661 | 19,550 | 180 | 60 | 33.56 | 9.21 | 25 |
99 | 4048 | 13,517 | 178 | 54 | 20.40 | 13.17 | 20 |
100 | 3007 | 34,021 | 351 | 65 | 114.52 | 10.32 | 30 |
Wavelet Decomposition Parameters | a5 | d5 | d4 | d3 | d2 | d1 |
---|---|---|---|---|---|---|
Energy Spectrum Coefficient | 98.17 | 0.20 | 0.19 | 0.48 | 0.38 | 0.59 |
Wavelet Decomposition Parameters | a5 | d5 | d4 | d3 | d2 | d1 |
---|---|---|---|---|---|---|
Energy Spectrum Coefficient | 98.72 | 0.18 | 0.01 | 0.12 | 0.23 | 0.68 |
Wavelet Decomposition Parameters | a5 | d5 | d4 | d3 | d2 | d1 |
---|---|---|---|---|---|---|
Energy Spectrum Coefficient | 97.89 | 0.28 | 0.15 | 0.22 | 0.41 | 1.05 |
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Li, G.; Zhao, Z.; Li, Y.; Li, C.-Y.; Lee, C.-C. Preprocessing Acoustic Emission Signal of Broken Wires in Bridge Cables. Appl. Sci. 2022, 12, 6727. https://doi.org/10.3390/app12136727
Li G, Zhao Z, Li Y, Li C-Y, Lee C-C. Preprocessing Acoustic Emission Signal of Broken Wires in Bridge Cables. Applied Sciences. 2022; 12(13):6727. https://doi.org/10.3390/app12136727
Chicago/Turabian StyleLi, Guangming, Zhen Zhao, Yaohan Li, Chun-Yin Li, and Chi-Chung Lee. 2022. "Preprocessing Acoustic Emission Signal of Broken Wires in Bridge Cables" Applied Sciences 12, no. 13: 6727. https://doi.org/10.3390/app12136727
APA StyleLi, G., Zhao, Z., Li, Y., Li, C.-Y., & Lee, C.-C. (2022). Preprocessing Acoustic Emission Signal of Broken Wires in Bridge Cables. Applied Sciences, 12(13), 6727. https://doi.org/10.3390/app12136727