Abstract
A novel balancing method for rotor based on unsupervised deep learning is proposed in this paper. The architecture of the proposed deep network is described. In the proposed network, compared to the supervised deep network, additional convolution layers are applied not only for the learning of the inverse mapping but also for identifying the unbalanced force without labeled data. The equivalent value and position of imbalances in two correction planes are obtained. A case study of a rotor with two discs supported by sliding bearings is conducted. Preset imbalances are balanced well by the proposed method. And, using the state values at different time intervals, no extra weight trails are needed. The results show that the proposed balancing method gives consideration to both cost and accuracy.
Highlights
Rotor balancing is a type of analysis that compares the vibration profile with the rotation of a mechanical element to characterize inconsistent weight distribution around the diameter while calculating the amount and position of the weight necessary to offset the net imbalance
As rotor imbalance may lead to malfunction, such as rotor rub-impact and bearing wear, and even to catastrophic failure [1], the rotor balancing is a traditional technology, but still important in nowadays rotor industry
Based on the loss function chosen, the training process is done by back propagation. e trainable variables are updated until the standard of the optimization is met. ird, the predicted unbalanced force should be fit to get the amplitude and phase of the harmonic type of force
Summary
Rotor balancing is a type of analysis that compares the vibration profile with the rotation of a mechanical element to characterize inconsistent weight distribution around the diameter while calculating the amount and position of the weight necessary to offset the net imbalance. As rotor imbalance may lead to malfunction, such as rotor rub-impact and bearing wear, and even to catastrophic failure [1], the rotor balancing is a traditional technology, but still important in nowadays rotor industry. Any mass that is not rotating around its center of mass will produce vibration. Asymmetry of the structure along the rotating axis and small changes in density and thickness of the material cause imbalances. Imbalance distribution leads to additional force and moment onto the rotor. Every single rotor needs several times of balancing like factory balancing [2] and onsite balancing [3] before implementation and online balancing [4] in working condition
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