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Rolling bearing's running state has an important influence on the health condition of rotate machinery. This work focuses on the remaining useful life prediction of the rolling bearing. An auxiliary particle filter-based predictor for rolling bearing is presented. The energy spectrum feature of vibration signal is selected as the representation of system degraded states. The wavelet packet decomposition...
Rolling bearing is one of the most commonly used components in rotating machinery. It's so easy to be damaged that it can cause mechanical fault. Thus, it is significant to study fault diagnosis technology on rolling bearing. In this paper, three deep neural network models (Deep Boltzmann Machines, Deep Belief Networks and Stacked Auto-Encoders) are employed to identify the fault condition of rolling...
Rolling bearing is one of the most commonly used components in rotating machinery. It is easy to be damaged which can cause mechanical fault. Thus, it is significance to study fault diagnosis technology on rolling bearing. This paper presents a Deep Boltzmann Machines (DBM) model to identify the fault condition of rolling bearing. A data set with seven fault patterns is collected to evaluate the performance...
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