CROSS-DEVICE INCREMENTAL BEARING FAULT DIAGNOSIS METHOD BASED ON CONTINUOUS LEARNING

• Main Authors: KONG, Lin, TAN, Luyang, ZHU, Zhongkui, LI, Lin, SHEN, Changqing, HUANG, Weiguo, SHI, Juanjuan, WANG, Dong, CHEN, Bojian
• Format: Patent
• Language: Chinese; English; French
• Published: 01.02.2024
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; MEASURING; PHYSICS; TESTING; TESTING STATIC OR DYNAMIC BALANCE OF MACHINES ORSTRUCTURES; TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR

A cross-device incremental bearing fault diagnosis method based on continuous learning. The method comprises: constructing a cross-device incremental bearing health state data set, and dividing same into diagnosis tasks of different stages according to devices (S101); constructing an initial diagnosis model by using diagnosis task data of the first device, and screening a typical case (S102); introducing neuron-level fine tuning and a classifier on the basis of the initial diagnosis model, so as to obtain a diagnosis model (S103); co-training the diagnosis model by using the typical case and bearing fault diagnosis task data of the next device, reducing, by using a loss function, the difference between the diagnosis model in the current stage and the diagnosis model in the previous stage in terms of diagnosis task data in the previous stage, and screening a typical case (S104); and repeating the step S104, and diagnosing bearing faults of all learned tasks by using the current diagnosis model, so as to obtain