Transformation of Guided Ultrasonic Wave Signals from Air Coupled to Surface Bounded Measurement Systems with Machine Learning Algorithms for Training Data Augmentation †
Abstract
1. Introduction
2. Methods and Experiments
2.1. Experimental Setup
2.2. Data Preprocessing
2.3. Machine Learning Models
3. Results and Discussion
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
GUW | Guided Ultrasonic Waves |
SHM | Structural Health Monitoring |
ML | Machine Learning |
ANN | Artificial Neural Network |
CNN | Convolutional Neural Network |
LSTM | Long Short-Term Memory |
AE | Auto Encoder |
ACMS | Air-Coupled Measurement System |
PWAS | Piezoelectric Wafer Active Sensor |
MEMS | Micro-Electro-Mechanical System |
PM | PWAS GUW Measurement |
AM | Air-Coupled GUW Measurement |
SSD | Single Signal Data |
ASD | Average Signal Data |
ARE | Averaged Relative Error |
SE | Signal Energy |
References
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Model | Layer Class | Parameters | Activation Function |
---|---|---|---|
ANN | Input | N: 6249; OS: [6249]; P: 0 | - |
Dense | N: 6249; OS: [6249]; P: 39056250 | tanh | |
Dense | N: 6249; OS: [6249]; P: 39056250 | linear | |
CNN | Input | N: 6249; OS: [6249]; P: 0 | - |
Conv1D | K: 16; KS: 12; S: 1; PC: valid; OS: [6227, 16]; P: 208 | tanh | |
Conv1D | K: 16; KS: 12; S: 1; PC: valid; OS: [6227, 16]; P: 3088 | tanh | |
Flatten | OS: [99632]; P: 0 | - | |
Dense | N: 6249; OS: [6249]; P: 622606617 | tanh | |
LSTM | Input | N: 6249; OS: [6249]; P: 0 | - |
LSTM | N: 3; OS: [6249, 3]; P: 60 | tanh | |
LSTM | N: 3; OS: [6249, 3]; P: 84 | tanh | |
LSTM | N: 3; OS: [6249, 3]; P: 84 | tanh | |
LSTM | N: 3; OS: [6249, 3]; P: 84 | tanh | |
LSTM | N: 3; OS: [6249, 3]; P: 84 | tanh | |
LSTM | N: 1; OS: [6249, 1]; P: 20 | tanh | |
TimeDistributed(Dense) | N: 1; OS: [6249, 1]; P: 2 | linear | |
ANN AE | Input | N: 6249; OS: [6249]; P: 0 | - |
Dense | N: 124; OS: [124]; P: 775000 | tanh | |
Dense | N: 64; OS: [64]; P: 7750 | tanh | |
Dense | N: 124; OS: [124]; P: 7812 | tanh | |
Dense | N: 6249; OS: [6249]; P: 781125 | linear | |
CNN AE | Input | N: 6249; OS: [6249]; P: 0 | - |
Conv1D | K: 64; KS: 4; S: 1; PC: same; OS: [6249, 64]; P: 320 | tanh | |
AveragePooling1D | PS: 10; S: 5; PC: same; OS: [1250, 64]; P: 0 | - | |
Conv1D | K: 64; KS: 4; S: 1; PC: same; OS: [1250, 64]; P: 16448 | tanh | |
Flatten | OS: [80000]; P: 0 | - | |
Dense | N: 1250; OS: [1250]; P: 100001250 | tanh | |
Reshape | OS: [1250, 1]; P: 0 | - | |
UpSampling1D | OS: [6250, 1]; P: 0 | - | |
Cropping1D | OS: [6249, 1]; P: 0 | - | |
Conv1DTranspose | K: 64; KS: 4; S: 1; PC: same; OS: [6249, 64]; P: 320 | tanh | |
Dense | N: 6249; OS: [6249, 1]; P: 65 | linear |
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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Polle, C.; May, D.; Bosse, S. Transformation of Guided Ultrasonic Wave Signals from Air Coupled to Surface Bounded Measurement Systems with Machine Learning Algorithms for Training Data Augmentation. Eng. Proc. 2024, 82, 119. https://doi.org/10.3390/ecsa-11-20448
Polle C, May D, Bosse S. Transformation of Guided Ultrasonic Wave Signals from Air Coupled to Surface Bounded Measurement Systems with Machine Learning Algorithms for Training Data Augmentation. Engineering Proceedings. 2024; 82(1):119. https://doi.org/10.3390/ecsa-11-20448
Chicago/Turabian StylePolle, Christoph, David May, and Stefan Bosse. 2024. "Transformation of Guided Ultrasonic Wave Signals from Air Coupled to Surface Bounded Measurement Systems with Machine Learning Algorithms for Training Data Augmentation" Engineering Proceedings 82, no. 1: 119. https://doi.org/10.3390/ecsa-11-20448
APA StylePolle, C., May, D., & Bosse, S. (2024). Transformation of Guided Ultrasonic Wave Signals from Air Coupled to Surface Bounded Measurement Systems with Machine Learning Algorithms for Training Data Augmentation. Engineering Proceedings, 82(1), 119. https://doi.org/10.3390/ecsa-11-20448