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Considering various health conditions under varying operational conditions, the mining sensitive feature from the measured signals is still a great challenge for intelligent fault diagnosis of spindle bearings. This paper proposed a novel energy-fluctuated multiscale feature mining approach based on wavelet packet energy (WPE) image and deep convolutional network (ConvNet) for spindle bearing fault...
The health monitoring and management applied for modern industrial machinery is a trend in intelligent industrial production. In this context, a novel health monitoring method based on a two-class model and nonlinear manifold learning is proposed to assess bearing performance degradation timely and reliably. This method does not need much historical operation information and can enhance the practicability...
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