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Machine Condition Classification Using Deterioration Feature Extraction and Anomaly Determination.

, and . IEEE Trans. Reliab., 60 (1): 41-48 (2011)

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Rotating Machinery Fault Diagnosis for Imbalanced Data Based on Fast Clustering Algorithm and Support Vector Machine., , , , , and . J. Sensors, (2017)Machine Condition Classification Using Deterioration Feature Extraction and Anomaly Determination., and . IEEE Trans. Reliab., 60 (1): 41-48 (2011)Comparison of random forest, artificial neural networks and support vector machine for intelligent diagnosis of rotating machinery., , , , and . Trans. Inst. Meas. Control, 40 (8): 2681-2693 (2018)Application of Wavelet Neural Networks on Vibration Fault Diagnosis for Wind Turbine Gearbox., , , and . ISNN (2), volume 5264 of Lecture Notes in Computer Science, page 313-320. Springer, (2008)Intelligent Diagnosis Method for Rotating Machinery Using Dictionary Learning and Singular Value Decomposition., , , and . Sensors, 17 (4): 689 (2017)Application of Fuzzy SOFM Neural Network and Rough Set Theory on Fault Diagnosis for Rotating Machinery., , , and . ISNN (3), volume 3498 of Lecture Notes in Computer Science, page 561-566. Springer, (2005)A novel adversarial learning framework in deep convolutional neural network for intelligent diagnosis of mechanical faults., , , and . Knowl. Based Syst., (2019)Study on Gas Turbine Thermodynamic Component Performance Degradation Assessment Based on RBF and SOM Neural Networks., , , and . IC-AI, page 52-57. CSREA Press, (2008)Deep transfer learning with limited data for machinery fault diagnosis., , , and . Appl. Soft Comput., (2021)Global geometric similarity scheme for feature selection in fault diagnosis., , and . Expert Syst. Appl., 41 (8): 3585-3595 (2014)