HLSM-KF-optimized identification algorithm of unbalanced vibration of dual-rotor in contra-rotating propfan.

A contra-rotating propfan consists of inner and outer propellers, having a dual inter-shaft bearing structure. The operating conditions are characterized by Slight Rotating Speed Differences (SRSDs) between the inner and outer rotors. These speed differences generate complex vibration transmission paths and harmonic cross-coupling between the dual rotors. Consequently, it becomes challenging to identify unbalanced vibration, leading to decreased low dynamic balance efficiency. Focusing on the prominent issues of low identification accuracy and poor stability in existing algorithms, mainly Least Square Method (LSM), Non-whole Beat Correlation Method (NWBCM), and Whole Beat Correlation Method (WBCM), when dealing with SRSDs under harmonic and noise interference, this paper introduces the Kalman Filter-Based Least Squares Identification Method for Filtering Harmonic Coupling (HLSM-KF). This method achieves precise, stable, and fast identification of unbalanced responses in contra-rotating rotors with SRSDs ranging from 1 to 30 rpm. Comparing the errors of the HLSM-KF algorithm to the other existing algorithms through simulations and experiments, the findings demonstrated that the identification accuracy and stability of the HLSM-KF algorithm are significantly dominant. Specifically, the Root Mean Square Error (RMSE) of the HLSM-KF algorithm is 47 % lower than that of the LSM algorithm. Therefore, a balancing experiment is conducted on the contra-rotating dual-rotor test rig, using the HLSM-KF algorithm. Consequently, the unbalanced vibrations of the inner and outer rotors are reduced by 86 % and 91 %, respectively, and the Root Mean Square (RMS) value of the whole system vibration is reduced by 87 %. [ABSTRACT FROM AUTHOR]