Machine Fault Diagnosis Using Audio Sensors Data and Explainable AI Techniques-LIME and SHAP
Source abstract
Abstract
Machine fault diagnostics are essential for industrial operations, and advancements in machine learning have significantly advanced these systems by providing accurate predictions and expedited solutions. Machine learning mod... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Fault Detection and Control Systems · Anomaly Detection Techniques and Applications · Industrial Vision Systems and Defect Detection
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (24)
Show source-provided references
1. Gearbox fault diagnosis based on deep recurrent neural networks
2. A new deep learning model for fault diagnosis with good anti-noise and domain adaptation ability on raw vibration signals
3. Machine fault diagnostics and condition monitoring using augmented reality and IoT
4. O. Das and D. B. Das, “Smart machine fault diagnostics based on fault specified discrete wavelet transform,” J. Braz. Soc. Mech. Sci. Eng., vol. 45, pp. 519–532, 2023. doi: 10.1007/s40430-022-03975-0.10.1007/s40430-022-03975-0 ↗
5. R. Sewada, A. Jangid, P. Kumar, and N. Mishra, “Explainable Artificial Intelligence (XAI),” Int. J. Food Nutr. Sci., vol. 10, pp. 1–15, 2023. doi: 10.36893/JNAO.2022.V13I02.041-047.10.36893/JNAO.2022.V13I02.041-047 ↗
6. Commentary on explainable artificial intelligence methods: SHAP and LIME
7. Explainable machine learning method for open fault detection of NPC inverter using SHAP and LIME
8. Software defects identification: Results using Machine Learning and Explainable Artificial Intelligence Techniques10.1109/ACCESS.2023.3329051 ↗
9. Acoustic emission sensor network based fault diagnosis of induction motors using a gabor filter and multiclass support vector machines
10. Linear discriminant analysis10.1007/978-1-4419-9878-1_4 ↗
11. Accurate identification of transformer faults from dissolved gas data using recursive feature elimination method10.1109/TDEI.2022.3215936 ↗
12. Application of semantic segmentation in high-impedance fault diagnosis combined with signal envelope and hilbert marginal spectrum for resonant distribution networks10.1016/j.eswa.2023.120631 ↗
13. Advancing high impedance fault localization via adaptive transient process calibration and multiscale correlation analysis in active distribution networks10.1016/j.measurement.2024.114431 ↗
14. Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence10.1016/j.inffus.2023.101805 ↗
15. Partial least squares
16. A hybrid deep learning approach: Integrating short-time Fourier Transform and continuous wavelet transform for improved pipeline leak detection10.3390/s23198079 ↗
17. A review of taxonomies of explainable artificial intelligence (XAI) methods
18. Random forests10.1023/A:1010933404324 ↗
19. Understanding IFRA for detecting synchronous machine winding short circuit faults based on image classification and smooth Grad-CAM++10.1109/JSEN.2022.3225210 ↗
20. Physics-informed interpretable wavelet weight initialization and balanced dynamic adaptive threshold for intelligent fault diagnosis of rolling bearings10.1016/j.jmsy.2023.08.014 ↗
21. Interpretable physics-informed domain adaptation paradigm for cross-machine transfer diagnosis
22. MIMII Due: Sound dataset for malfunctioning industrial machine investigation and inspection with domain shifts due to changes in operational and environmental conditions
23. Bearing fault diagnosis based on statistical locally linear embedding10.3390/s150716225 ↗
24. Hybrid deep transfer learning architecture for industrial fault diagnosis using Hilbert transform and DCNN-LSTM10.1007/s11227-022-04830-8 ↗