Fault Diagnosis Method of Planetary Gearboxes Based on Multi-scale Convolution Neural Network

As an important transmission part, planetary gearbox is mainly used to output power and change the transmission power ratio of the whole transmission system. It is widely used in various complex mechanical equipment. Because the planetary gearbox often operates under heavy load and high speed, the gears and bearings will inevitably wear and malfunction, which will cause casualties and economic losses in serious cases. In order to accurately diagnose the fault of planetary gearbox, this paper design a fault diagnosis method based on multi-scale convolution neural network, and built a fault diagnosis simulation test-bed. At the same time, this paper compares the diagnosis accuracies of the multi-scale convolutional neural network with the traditional convolutional neural network and multi-core convolutional neural network. The result shows that the multiscale convolutional neural network has high recognition accuracy and is suitable for the fault diagnosis of planetary gearbox.