A Fault Diagnosis Approach for Rotating Machinery Rotor Parts Based on Equipment Operation Principle and CEEMD
Keywords:fault diagnosis, rotor parts fly-off, equipment operation principle, Complementary Ensemble Empirical Mode Decomposi-tion (CEEMD), Industrial Big Data Challenge 2019
Aiming at the problem of fault diagnosis of rotor parts of large rotating machines, a fault diagnosis approach based on the equipment operation principle and the Complementary Ensemble Empirical Mode De-composition (CEEMD) method is proposed. First, the vibration displacement data of the rotor in each direction during the operation of rotating mechanical equipments are pre-processed; then, the vibration data, in the effective smooth operation stage based on the equipment operation principle, are selected for Empirical Mode Decomposition (EMD) and CEEMD analysis methods to evaluate the equipment operation status; finally, vibration data are analyzed to extract dimensionless statistical indicators by the Intrinsic Mode Function (IMF) component. The effectiveness of the proposed approach is verified by the prognostic dataset of rotor parts fly-off in the Industrial Big Data Challenge 2019. From the experimental result, fault diagnosis of rotor components of large rotating machinery is successfully realized by establishing the proposed approach.