Identification of Gearbox Health Status Based on Deep
Gearbox is a crucial transmission component in many types of mechanical equipment,and recognizing its operation is of utmost importance to ensure the stability and safety of the equipment.To accurately assess the health status of gearboxes,a method of identifying the gearbox health state was put forward based on deep convolution-al neural network(DCNN).Firstly,the collected vibration signal of the gearbox was denoised by using Variational Mode Decomposition(VMD)and Wavelet Threshold(WT).Secondly,linear and nonlinear feature extraction was per-formed on the signal.Finally,a DCNN was used to construct a model to identify the health state of the gearbox.Exper-iment results demonstrate that the proposed method achieves a correct recognition rate of over 97.5%for the health status of the gearbox.
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