Particle swarm optimization method for two-stage transmission scheme based on fuzzy matter element
A particle swarm optimization and fuzzy matter-element technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as slow convergence speed and low quality
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Embodiment 1
[0074] refer to figure 1 , figure 2 , a particle swarm optimization method based on a fuzzy matter-element two-stage transmission scheme, the method mainly includes the following steps:
[0075] (1) Initialize the population of transmission schemes, and the number of schemes is defined as m:
[0076] Organization code
institution name
Common transmission ratio range
Maximum transmission
1
Ordinary flat belt drive
2~4
6
2
Ordinary V belt transmission
2~4
15
3
friction wheel drive
2~6
20
4
roller chain drive
2~5
10
5
toothed chain drive
2~5
10
6
Cylindrical gear drive
3~5
10
7
Bevel gear drive
2~3
8
8
7~40
80
9
planetary gear transmission
3~83
500
[0077] Table 1
[0078] Representation of particles
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Embodiment 2
[0129] see figure 1 , figure 2 , the particle swarm optimization method of the fuzzy matter-element-based two-stage transmission scheme in this embodiment is the same as that in Embodiment 1. The design requirements of the transmission scheme of this embodiment are: input speed 960r / min; output speed 78r / min; transmission power 4.3kW; transmission efficiency not less than 0.85;
[0130] Select the transmission scheme: ① high transmission efficiency, ② good working stability, ③ long service life, ④ good environmental adaptability, ⑤ low cost and other indicators as design goals.
[0131] Use the particle swarm optimization algorithm to solve the design problem of the reducer. The population size is m=20, and the maximum number of generations is 200 generations. Comparing the particle swarm optimization algorithm (PSO) with the genetic algorithm (GA), the maximum fitness curve of the two figure 2 shown.
[0132] from figure 2 It can be seen that both methods have found th...
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