An improved Lempel-Ziv complexity indicator based on multiscale decomposition and multiscale encoding for bearing failure severity recognition

Lempel-Ziv complexity has been widely applied in multiple fields, and there are numerous improvements in multiscale computation and encoding to enhance its ability to characterize signal changes. Based on the hierarchical analysis, this paper proposes an improved Lempel-Ziv indicator based on multiscale decomposition and multiscale encoding, which is applied to the recognition of bearing failure severity. The signal is first decomposed into multiple scales through hierarchical analysis. Next, the decomposed node signal is further decomposed by coarse-grained methods. Then, the multiscale decomposed signal is further decomposed into low-frequency and high-frequency components using hierarchical analysis and the multiscale encoding is performed based on the decomposed low-frequency and high-frequency components. Finally, the Lempel-Ziv complexity is calculated based on multiscale encoding. The effectiveness of the proposed method is validated by three single-point bearing fault datasets with different failure severity. The proposed method can achieve a classification accuracy of over 97%. The proposed method can be effectively applied to classify the bearing failure severity.