Pipeline fault diagnosis method based on convolutional neural network

The invention provides a pipeline fault diagnosis method based on a convolutional neural network. The method is characterized in that external force is applied to a to-be-detected pipeline, and measurement excitation response signals are collected at test points of the pipeline; after the collected measurement signals are subjected to noise reduction, pipeline fault feature signals are extracted and are subjected to standard treatment; and then the fault signals are divided into a training set and a test set to be input to a pipeline fault diagnosis model based on the convolutional neural network for fault identification and classification. The fault identification and diagnosis capability can be improved. The pipeline fault diagnosis model method can quickly and accurately identify the fault state of the pipeline according to the learning and identifying capabilities of the convolutional neural network, and the great significance is achieved for accurate monitoring and early warning of pipeline leakage. 本发明提