IEEE Access (Jan 2023)

Multi-Objective Optimization Design of Low Specific Speed Centrifugal Pumps Based on Genetic Algorithm

  • Yuqin Wang,
  • Luxiang Zhou,
  • Shimin Zheng

DOI
https://doi.org/10.1109/ACCESS.2023.3311893
Journal volume & issue
Vol. 11
pp. 97896 – 97908

Abstract

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Aiming at the problems of low working efficiency and high energy loss in the operation of centrifugal pump, an intelligent algorithm for centrifugal pump design was proposed. On the basis of hydraulic design, a multi-objective optimization mathematical model of centrifugal pump was established. A Genetic algorithm (GA) was designed to optimize the major structural parameters of the pump and the optimal combination of parameters was obtained. Calculation results suggested that the optimized pump efficiency was significantly augmented and the energy loss was significantly lower. The external characteristics test platform of centrifugal pump was established. The test results indicated that the head, efficiency and energy loss of the pump had been effectively improved after optimization. Under the rated working conditions, the centrifugal pump based on GA algorithm had increased the head by 26.92%, boosted the efficiency by 32.28%, and diminished the energy loss by 14.38%, which achieved the expected goal. Obviously, the GA algorithm is significantly better than the Particle Swarm Optimization (PSO) algorithm in improving the performance of centrifugal pump. The accuracy and superiority of the designed GA algorithm were verified. This served a reference for the future design of pumps with high efficiency and low energy consumption.

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