Gearbox input shaft bearing life prediction method, apparatus and device

Abstract

The application discloses a gearbox input shaft bearing life prediction method, device and equipment, and relates to the technical field of gearboxes. The method comprises the following steps: converting the segmented gearbox input shaft bearing vibration signal into a vibration image, and extracting a sample vibration image; determining a physical model life index based on a life prediction physical model, labeling a preset number of sample vibration images to obtain labeled vibration images and unlabeled vibration images; performing feature extraction on the labeled vibration images and the unlabeled vibration images to obtain a feature representation vector; calculating a comprehensive evaluation index of the feature representation vector, and when the comprehensive evaluation index is greater than or equal to an evaluation index threshold, fusing the feature representation vector to obtain a fusion feature; and determining a life prediction result of the gearbox input shaft bearing based on the fusion feature. In the foregoing manner, the advantages of deep learning and physical models are combined to predict the life of the gearbox input shaft bearing, thereby improving the accuracy and reliability of the prediction.

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