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Effective fault diagnosis has long been a research topic in the prognosis and health management of rotary machinery engineered systems due to the benefits such as safety guarantees, reliability improvements, and economical efficiency. This paper investigates an effective and reliable deep learning method known as stacked denoising autoencoder (SDA), which is shown to be suitable for certain health...
This paper presents a rolling bearing fault diagnosis approach based on the combination of Ensemble Empirical Mode Decomposition (EEMD), Information Entropy (IE) and Support Vector Machine (SVM). The horizontal and vertical vibration signals of the bearings are utilized as the input of the method. First, the signals, after preprocess, are decomposed into certain number of intrinsic mode functions...
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