Optimal Design of Sliding Bearings Based on Artificial Intelligence Algorithm and CFD Simulation

Sliding bearings have a long history, simple manufacturing, and low cost. However, the function of sliding bearings is very large. As a key component of rotating machinery, thrust sliding bearing is directly related to the overall performance of the machine. The machines that can be seen in life, whether simple or complicated, have been used. However, with the development of science and technology and economy, all kinds of new things have been inoculated. One of the current issues is how sliding bearings can continue to keep machinery stable. CFD is the abbreviation of English computational fluid dynamics (computational fluid dynamics). It is developed with the development of computer technology and numerical computing technology. Simply put that CFD is equivalent to “virtually” doing experiments on the computer to simulate the actual fluid flow. The purpose of this article is to study the optimal design of sliding bearings by artificial intelligence algorithms and CFD simulation. This paper uses intelligent design methods to optimize the appearance, shape, and manufacturing process of sliding bearings and to carry the bearing capacity, friction coefficient and temperature rise of sliding bearings. Comprehensive research then establishes the objective function. The finite element algorithm, genetic algorithm, and matrix theory are used to calculate the stability of the sliding bearing under various conditions. The artificial intelligence algorithm is used to sort the calculated data. The CFD simulation is used to obtain the most reasonable result. Algorithm, as well as the appearance, shaft diameter, and material of the plain bearing, maintains stability under various conditions. The experimental data show that the classification using artificial intelligence algorithms and CFD simulation can significantly improve the performance of sliding bearings. It is found that the relationship between the sliding bearings is related to the speed, the diameter of the bearing, and other factors. Experimental data show that artificial intelligence algorithms and CFD simulation can provide reliable data references for the optimal design of sliding bearings, and the optimized sliding bearings can meet the stability under relevant conditions.