**4. Conclusion**

The chaotic system of rolling bearing is discussed, and the vibration signal of rolling bearing is changed by fast Fourier. It is found that different chaotic phenomena appear in different working conditions. Therefore, a fault diagnosis method of rolling bearings based on entropy features is proposed, and the relationship between approximate entropy, sample entropy, information entropy, and the maximum Lyapunov exponent is studied. It is concluded that single entropy can't improve the chaotic phenomenon. Furthermore, a fault extraction method of rolling bearing combining approximate entropy, characteristic entropy, and information entropy is proposed. The feasibility of this method is proved by the comparative experiment of single entropy and approximate entropy sample entropy information entropy joint analysis. In the final test, the classification accuracy reached 98.28%. The feasibility of this method is proved, and four working conditions of rolling bearings are diagnosed with high precision.
