DING Guo-jun, WANG Li-de, SHEN Ping, et al. Sensor fault diagnosis based on EEMD energy entropy and LSSVM[J]. 2013, 32(7): 22-25. DOI: 10.13873/j.1000-97872013.07.039.
As key components of electric multiple units(EMUs)brake system
sensor has significant impact on security and reliability of EMUs operation.Ensemble empirical mode decomposition(EEMD)overcomes the shortcoming of mode mixing of EMD
and the decomposed intrinsic mode functions(IMFs)prominent the local features of fault
and solve energy entropy
to form fault feature vector
then input to least squares support vector machine(LSSVM)for fault identification and classification
at the same time
particle swarm optimization(PSO)algorithm is applied for optimizing the structure parameters of LSSVM.The test result indicates that the fault diagnosis model has high correct classification rate for AS pressure sensor fault of EMUs.