Abstract
As the flow structure in the centrifugal pump is complicated, it always causes serious noises, which has become an important problem in environmental protections. Some works have been completed for optimizing and reducing radiated noises of centrifugal pumps, but optimized algorithms are traditional and easily fall into local extreme values, so that final results are not always the optimal. For overcoming disadvantages of traditional algorithms, this paper proposed a novel MLGA-PSO (Multi-layer Genetic Algorithm-Particle Swarm Optimization) algorithm to make an optimization for noises and hydraulic performance of centrifugal pumps. This algorithm starts from the organizational structure of individuals and separates the global search from the local search, which can not only accelerate the convergence speed, but also avoid reducing the global search ability. The algorithm could effectively overcome the contradiction between global search ability and convergence speed. Inlet diameter, impeller blade outlet width, blade outlet angle and amount of blades are as designed variables. In order to verify advantages of the proposed MLGA-PSO algorithm in global search ability, optimizing speed and stability, GA (Genetic Algorithm), PSO (Particle Swarm Optimization) and GA-PSO (Genetic Algorithm-Particle Swarm Optimization) algorithms are chosen to carry out the compared experiment. Results show that the proposed MLGA-PSO algorithm has higher efficiency and accuracy. Finally, total noises of the optimized noise in the near-field and far-field using MLGA-PSO algorithm are 181 dB and 74 dB, respectively. Total noises in the near-field are reduced by 4.7 %, while those in the far-field are reduced by 16.9 %. It is clearly that the optimized centrifugal pump presents an obvious noise reduction effect.
Highlights
At present, centrifugal pumps have become a main equipment to be used for energy recovery
For overcoming disadvantages of traditional optimization algorithms, this paper combines a novel MLGA-Particle Swarm Optimization (PSO) algorithm with numerical simulation technologies to conduct a multi-objective optimization for flow noises and hydraulic performance of the centrifugal pump, where parameters including inlet diameter, impeller blade outlet width, blade outlet angle and amount of blades are as designed variables
Contours of radiated noises of the optimized centrifugal pump were extracted as shown in Fig. 18 and Fig. 19, and they were compared with the original one, showing that the radiated noise was obviously reduced
Summary
Centrifugal pumps have become a main equipment to be used for energy recovery. Studied results show that flow-induced noises under different flow rates contain characteristic frequencies, and include a low-frequency broadband spectrum These reported researches only conducted a parametric analysis on flow noises of centrifugal pumps, but did not apply algorithms to optimize flow-induced noises of centrifugal pumps. With 4 indexes including sound pressure levels of blade frequency noises, head lift, efficiency and shaft power as the standard, Si [18] adopted the weight matrix method to complete a multi-objective optimization design on the impeller. For overcoming disadvantages of traditional optimization algorithms, this paper combines a novel MLGA-PSO algorithm with numerical simulation technologies to conduct a multi-objective optimization for flow noises and hydraulic performance of the centrifugal pump, where parameters including inlet diameter, impeller blade outlet width, blade outlet angle and amount of blades are as designed variables. Results show that both the optimized efficiency and accuracy are improved
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