High-speed train wheel set bearing fault diagnosis and prognostics: Research on acoustic emission detection mechanism. (1st November 2022) - Hou, Dongming; Qi, Hongyuan; Li, Defa; Wang, Cuiping; Han, Defu; Luo, Honglin; Peng, Chang
Highlights: A force analysis of the whole, local, and single roller is performed based on the Hertz contact theory and the structure and load characteristics of high-speed train wheel set bearings (HSTWSB). An AE mathematical model of HSTWSB considering the asperity elastic deformation, elastohydrodynamic lubrication and signal attenuation is established. The improved models corresponding to different damage types considering the influences of speed, load, deformation, and defect morphology are established. Comparison results between the theoretically calculated and experimental values verify the correctness of the proposed models. Abstract: Acoustic emission (AE) technology is suitable for the condition monitoring and fault diagnosis of high-speed train wheel set bearings (HSTWSB) owing to its high frequency and high sensitivity. However, there has been no research on the mechanism of the relationship between HSTWSB state and AE signal. Therefore, this study explores the AE detection mechanism of HSTWSB state. First, based on the structure and load characteristics of HSTWSB, combined with the Hertz contact theory, a force analysis of the whole, local, and single roller is performed. Second, based on the assumption of random distribution of asperities, a contact model of the rough surface of the bearing is established, and the elastic deformation analysis of the asperities under load is performed based on the theory of elasticity. The corresponding relationship between the asperity deformation energy and root mean square (RMS) of the AE signal is obtained. Meanwhile, considering the influence of elastohydrodynamic lubrication (EHL) and signal attenuation on the deformation energy, an AE mathematical model of the HSTWSB is established. Accordingly, based on the characteristics of HSTWSB with different damage types, the influences of the load, deformation, speed, and defect morphology on the AE signals are thoroughly analyzed, and the improved models corresponding to different damage types are established, which extends the AE model to greater freedom. Finally, taking different damage types of the outer ring fault bearings as examples, the correctness of the proposed models is verified by comparing the theoretically calculated and experimental results. The proposed models can provide theoretical support for the application of AE to bearing condition monitoring.