Abstract
Abstract Due to the complicated working conditions of the ship stern-shaft mechanical seals, it is very difficult to evaluate and optimize the temperature on the sealed end faces. In the paper, one FEA model of the small taper convergent stern-shaft mechanical seals was put forward, and the nonlinear end-face liquid film pressure distribution was derived from different end-face gaps based on the simplified Reynolds equation as the end-face input parameters in FEA model. To prove the correction of the FEA results, one experiment was designed and completed. At the same time, combined with a parametrically coupled FEA model and an orthogonal experimental design, one PSO-BP-GA method based on the combination of particle swarm optimization (PSO), BP neural network and genetic algorithm (GA) was proposed to optimize the temperature of the sealed end faces. The results show that aiming at the prediction accuracy of the temperature on the sealed end faces, the PSO-BP algorithm is higher than BP algorithm and GA-BP algorithm, which error interval is shortened about 40% and 29%, respectively. Subsequently, PSO-BP-GA algorithm is obviously better than BP-GA algorithm and GA-BP-GA algorithm, which validates its effectiveness and feasibility. It will help to lay a theoretical foundation for temperature evaluation on the sealed end faces.
Highlights
Due to the complicated working conditions of the ship stern-shaft mechanical seals, it is very difficult to evaluate and optimize the temperature on the sealed end faces
One FEA model of the small taper convergent stern-shaft mechanical seals was put forward, and the nonlinear end-face liquid film pressure distribution was derived from different end-face gaps based on the simplified Reynolds equation as the end-face input parameters in FEA model
At the same time, combined with a parametrically coupled FEA model and an orthogonal experimental design, one PSO-BP-GA method based on the combination of particle swarm optimization (PSO), BP neural network and genetic algorithm (GA) was proposed to optimize the temperature of the sealed end faces
Summary
Abstract: Due to the complicated working conditions of the ship stern-shaft mechanical seals, it is very difficult to evaluate and optimize the temperature on the sealed end faces. The finite difference method was used to solve the control equations for the fluid pressure and temperature of the seal end faces, and the finite element method was used to determine the thermal deformation state of the seals All these could be applied for mechanical seal design and optimization. In view of the unique large size and high pressure of the ship stern-shaft mechanical seals, the paper adopted an orthogonal experimental design and ANSYS parametric simulation technology in order to establish one strong non-linear overall mapping relation between the given design variables and objective function. It can find the global optimum within the scope of design variables and objective function in order to achieve optimization purposes All this proposes a stern-shaft mechanical seals optimization design method based on PSO-BP-GA method, which can quickly obtain the critical dimensions of the sealed end faces to verify the feasibility of the optimization method
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