Research on remaining life prediction of bearings based on CDBN-BIGRU

Bearings are widely used in various fields of industry, and their reliability will directly affect the performance and lifetime of equipment as they are wearable components and need to be replaced regularly. So the study on remaining life prediction of bearings has great research value. We propose a CDBN-BIGRU bearing remaining life prediction model based on artificial intelligence methods, which achieves the feature extraction and information filtering of vibration signals, and establishes the time series relationship between the signal features, so as to reflect the operation of bearings in different time periods and the intrinsic correlation in a more detailed way. This method effectively improves the prediction accuracy belongs to the remaining life of bearings. The experiments show that CDBN-BIGRU model we proposed get better result than other methods, which improved the accuracy and F1 score value. Based on the current research progress, We will continue to promote the research on the robustness of the remaining life prediction model in the future work.