Convolutional Neural Network and Motor Current Signature Analysis during the Transient State for Detection of Broken Rotor Bars in Induction Motors
Abstract
:1. Introduction
2. Theoretical Background
2.1. Motor Current Signature Analysis
2.2. Infinite Impulse Response (IIR) Notch Filter
2.3. Fourier Transform
2.4. Convolutional Neural Network
3. Proposed Methodology
4. Experimentation and Results
4.1. Experimental Setup
4.2. Signal Processing Results
4.3. Convolutional Neural Network Results
4.4. Comparison with Previous Works
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Name | Type | Activations | Learnables |
---|---|---|---|
Input | Image input | 25 × 25 × 1 | - |
Conv_1 | Convolution | 23 × 23 × 8 | Weights 3 × 3 × 1 × 8 and Bias 1 × 1 × 8 |
Relu1 | Rectified linear unit | 23 × 23 × 8 | - |
2 × 2-MP | Max pooling | 11 × 11 × 8 | - |
Conv_2 | Convolution | 9 × 9 × 8 | Weights 3 × 3 × 8 × 8 and Bias 1 × 1 × 8 |
Relu2 | Rectified linear unit | 9 × 9 × 8 | - |
FC | Fully connected | 1 × 1 × 4 | Weights 4 × 648 and Bias 4 × 1 |
SM | Softmax | 1 × 1 × 4 | - |
Class | Classification output | - | - |
Target Class | |||||
---|---|---|---|---|---|
Predicted class | HLT | HBRB | 1BRB | 2BRB | |
HLT | 25 | 0 | 0 | 0 | |
HBRB | 0 | 25 | 0 | 0 | |
1BRB | 0 | 0 | 25 | 0 | |
2BRB | 0 | 0 | 0 | 25 | |
Total accuracy (%) | 100 |
Work | Proposed Methods | Damage Level | Accuracy (%) |
---|---|---|---|
[9] | 1. Feature extraction is performed by using Homogeneity analysis 2. Gaussian probability density function is employed as classifier. | HBRB, 1- and 2BRB | 99 |
[10] | 1. Features extraction is performed by using MUSIC technique 2. Bayes method is employed as classifier. | 1- and 2BRB | 100 |
[12] | 1. Features extraction is performed by using Wavelet and Hilbert transforms. 2. Linear discriminant technique is employed as classifier. | 1- and 2BRB | 100 |
[23] | 1. Feature extraction is performed by using Fractal dimension 2. Fuzzy logic is employed as classifier. | HBRB, 1- and 2BRB | 95 |
[26] | 1. Features extraction is performed by using extended Kalman filter 2. MUSIC technique is employed as classifier. | HBRB and 1BRB | 100 |
[43] | 1. Wavelet transform is used to transform the measured signals to images. 2. A CNN is employed as features estimator and classifier. | 3BRB | 99 |
[70] | 1. Features extraction is performed by using Wavelet transform. 2. Correlation Pearson is employed as classifier. | HBRB, 1- and 2BRB | 95 |
[71] | 1. Feature extraction is performed by using Hilbert transform. 2. Gaussian probability density function is employed as classifier. | HBRB, 1- and 1½BRB | 99 |
Proposed work | 1. Short time Fourier transform is used to transform the measured signals to images. 2. A CNN is employed as features estimator and classifier. | HBRB, 1- and 2BRB | 100 |
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Valtierra-Rodriguez, M.; Rivera-Guillen, J.R.; Basurto-Hurtado, J.A.; De-Santiago-Perez, J.J.; Granados-Lieberman, D.; Amezquita-Sanchez, J.P. Convolutional Neural Network and Motor Current Signature Analysis during the Transient State for Detection of Broken Rotor Bars in Induction Motors. Sensors 2020, 20, 3721. https://doi.org/10.3390/s20133721
Valtierra-Rodriguez M, Rivera-Guillen JR, Basurto-Hurtado JA, De-Santiago-Perez JJ, Granados-Lieberman D, Amezquita-Sanchez JP. Convolutional Neural Network and Motor Current Signature Analysis during the Transient State for Detection of Broken Rotor Bars in Induction Motors. Sensors. 2020; 20(13):3721. https://doi.org/10.3390/s20133721
Chicago/Turabian StyleValtierra-Rodriguez, Martin, Jesus R. Rivera-Guillen, Jesus A. Basurto-Hurtado, J. Jesus De-Santiago-Perez, David Granados-Lieberman, and Juan P. Amezquita-Sanchez. 2020. "Convolutional Neural Network and Motor Current Signature Analysis during the Transient State for Detection of Broken Rotor Bars in Induction Motors" Sensors 20, no. 13: 3721. https://doi.org/10.3390/s20133721
APA StyleValtierra-Rodriguez, M., Rivera-Guillen, J. R., Basurto-Hurtado, J. A., De-Santiago-Perez, J. J., Granados-Lieberman, D., & Amezquita-Sanchez, J. P. (2020). Convolutional Neural Network and Motor Current Signature Analysis during the Transient State for Detection of Broken Rotor Bars in Induction Motors. Sensors, 20(13), 3721. https://doi.org/10.3390/s20133721