The invention discloses a dual-model fault diagnosis method based on dynamic weighing. The method comprises the steps that sensor vibration signals and fault recording texts collected by a motor driveend under the normal state and various fault states are selected; then,the sensor vibration signals and the fault recording texts are learned,then,a dynamic weighing combination algorithm is adoptedfor giving a weight to a model,sub-model SVM multi-classification voting results are combined,and a final classification result is obtained. Joint diagnosis for bearing fault data and bearing fault texts can be achieved. Non-balanced processing and valuable information extraction and classification are performed on equipment operation data,manual recording experience knowledges are effectively combined for text data mining,compared with a single diagnosis model,the method can remarkably improve the fault diagnosis precision,a better performance evaluation index is obtained,and the good theoretic and application value is obtained.