Computer Aided Evaluation of Fir Tree Blade Root Profile Based on Particle Swarm Algorithm
Aiming at the problems of inefficiency and inaccuracy in the evaluation of fir tree blade root profile, a method of computer aided profile evaluation based on particle swarm algorithm is proposed. The evaluation process is automated by this method, the theoretical profile and the coordinates of the...
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| Published in | Journal of physics. Conference series Vol. 1237; no. 2; pp. 22146 - 22152 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Bristol
IOP Publishing
01.06.2019
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1742-6588 1742-6596 1742-6596 |
| DOI | 10.1088/1742-6596/1237/2/022146 |
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| Summary: | Aiming at the problems of inefficiency and inaccuracy in the evaluation of fir tree blade root profile, a method of computer aided profile evaluation based on particle swarm algorithm is proposed. The evaluation process is automated by this method, the theoretical profile and the coordinates of the measured points are read automatically, the measured points and the theoretical profile are aligned automatically, the profile deviation is calculated, and whether the blade root is qualified is determined. The mathematical model and calculation method of profile evaluation are given, the measured points and theoretical profile are aligned precisely according to the principle of least square by making use of the particle swarm optimization algorithm with adaptive inertia weight(APSO) after coarse alignment, and the influence of position error between design reference and measurement reference on the results of profile evaluation is eliminated. Simulation experiment and practical application manifest better accuracy and stability can be obtained by using APSO algorithm compared with other algorithms when evaluating the fir tree blade root profile. The computer aided profile evaluation method proposed in this paper could totally replace the traditional manual method. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1742-6588 1742-6596 1742-6596 |
| DOI: | 10.1088/1742-6596/1237/2/022146 |