Method and device for training bearing fault diagnosis model, equipment and storage medium

The invention provides a method and device for training a bearing fault diagnosis model, equipment and a storage medium, and the method comprises the steps: obtaining a plurality of bearing vibration data sets under different fault types of a source domain and a target domain, and obtaining a source domain data set and a target domain data set; an initial bearing fault diagnosis model is constructed, the initial bearing fault diagnosis model comprises a distribution difference measurement and health state classifier, and the distribution difference measurement and health state classifier is used for classifying the health state of the bearing; and training the initial bearing fault diagnosis model through the source domain data set and the target domain data set to obtain a bearing fault diagnosis model. Through the method, the effect of improving the bearing detection accuracy of the bearing fault diagnosis model can be achieved. 本申请提供一种训练轴承故障诊断模型的方法、装置、设备和存储介质，该方法包括，分别获取源域和目标域不同故障类型下的多个轴承振动数据集合，得到源域数据集和目标域数