Search Results (2)

Bearing rings are thin-walled components prone to distortion during quenching. Achieving high-precision distortion control for bearing rings remains a critical challenge in high-precision bearing manufacturing. This paper proposes an AI-driven method for distortion control during bearing ring quenching in mesh-belt furnaces. The primary objective is to identify the optimal reverse motor frequency within the furnace. An experimental database is established using distortion results obtained at different reverse motor frequencies. This database serves as training data for deep learning. Subsequently, a large language model (LLM) employs few-shot learning to optimize and predict the reverse motor frequency influencing bearing quenching distortion. Results demonstrate that the LLM method achieves significantly higher prediction accuracy than traditional machine learning approaches. The optimization outcomes validate the effectiveness of generative AI in optimizing the reverse motor frequency of mesh-belt furnaces and controlling distortion during bearing ring quenching. Full article

Bearings are usually used at high-speed and high-load conditions, so the bearing sleeve must be able to withstand large contact stress, which requires heat treatment. However, during the quenching process of the bearing sleeve, a vapor film is formed on the surface. Since the vapor film is not uniform along the axial direction during the process of boiling and breaking, it will cause uneven distortion of the bearing sleeve. This uneven distortion will cause the outer ring of the bearing to have elliptical distortion after heat treatment. However, the mechanism of this problem and how to reduce the elliptical distortion has not been completely solved. In this paper, two points on the inner wall and outer wall of the bearing sleeve in the orthogonal direction are measured by means of experiments, and the mechanism of the ellipticity distortion during the quenching process is revealed. Additionally, through its horizontal placement, oblique placement, and vertical placement, the cooling curve and cooling rate curve changes in the process of entering the quenching agent are studied; based on the cooling curve, the heat transfer coefficient of the bearing sleeve during quenching is obtained by the heat transfer equation. Input the heat transfer coefficient into the CAE heat treatment simulation software COSMAP, according to the Metallo-Thermo-Mechanics theory and the method of multi-field coupling, simulating the quenching process of GCr15 and 16MnCr5 materials. By comparison, the ellipticity value of the bearing placed at a 45° angle is smaller than that of the horizontally and vertically placed bearings, with the 16MnCr5 material having the smallest ellipticity value of 0.00016. The simulation results verified the distortion mechanism of the bearing sleeve during the quenching process and how to reduce the solution of elliptical distortion. Full article