Load recognition of connecting-shaft rotor system under complex working conditions.

A method for qualitatively recognizing the load of the rolling equipment's connecting-shaft rotor system is proposed in this paper due to the complexity of rolling production conditions and the limitations of single source response signals. The method is oriented towards fusing the vibration and motor's current information. First, singular value decomposition and wavelet packet analysis are used to preprocess the two types of response signals. Then, the Bayesian estimation method in feature-level fusion achieves qualitative recognition and analysis of rotor system load types. Corresponding load experiments are completed on a load recognition test platform based on vibration and the motor's current signals. The research results show that the load recognition method based on fusion information can recognize the type of load excitation with a recognition accuracy of 91.7 %, higher than other single-source response signal methods. Therefore, the feasibility of the aforementioned theoretical methods is verified.