基于粗糙集理论的螺旋桨设计规则提取

胡豹; 高永卫; 魏斌斌

doi:10.13224/j.cnki.jasp.20210645

基于粗糙集理论的螺旋桨设计规则提取

doi: 10.13224/j.cnki.jasp.20210645

胡豹^1,,
高永卫^1,*, ,,
魏斌斌²

1.
西北工业大学航空学院，西安 710072
2.
西安交通大学航天航空学院，西安 710049

详细信息

作者简介:
胡豹（1995-），男，博士生，主要从事螺旋桨智能设计研究。E-mail：hu_bao@mail.nwpu.edu.cn

通讯作者:
高永卫（1968-），男，教授、博士生导师，博士，主要从事设计空气动力学、实验空气动力学和气动噪声研究。E-mail：gyw630@nwpu.edu.cn

中图分类号: V211.44
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- 被引次数: 0
出版历程
- 收稿日期: 2021-11-09
- 网络出版日期: 2023-06-05

Propeller design rule extraction based on rough set theory

HU Bao^1
,,
GAO Yongwei^{1,*
, ,},
WEI Binbin²

1.
School of Aeronautics，Northwestern Polytechnical University，Xi’an 710072，China
2.
School of Aerospace Engineering，Xi’an Jiaotong University，Xi’an 710049，China

摘要

摘要:
不同于由专家通过理论推导或经验得到设计规则的传统方法，提出了数据驱动的螺旋桨设计规则提取方法。使用粗糙集理论对螺旋桨优化设计过程中产生的大量方案数据进行分析，发展了适当的属性表示方法和属性离散方法。结果表明：在对两类不同参数螺旋桨型号的研究中，均提取出了“当各剖面诱导速度的差异越小时，螺旋桨效率越高”的设计规则，这一规则与Betz条件相当，验证了方法的有效性。基于数据驱动的螺旋桨设计规则提取方法可为后续三维设计规则的发现和优化设计研究提供技术支持，该思想也可供其他设计领域参考。
- 规则提取 /
- 螺旋桨设计 /
- 数据驱动 /
- 粗糙集理论 /
- Betz条件
Abstract:
Different from the traditional method of obtaining design rules by experts through theoretical derivation or experience, a data-driven propeller design rule extraction method was proposed. The rough set theory was used to analyze a large number of scheme data generated in the process of propeller optimization design. An appropriate attribute representation method and an attribute discrete method were developed. Result showed that, in the study of two types of propeller models with different parameters, the design rule that the smaller the difference of the induced velocity of each section of the propeller, the higher the propeller efficiency was extracted. This rule was equivalent to the Betz condition, which verified the effectiveness of the method. The data-driven propeller design rule extraction method can provide technical support for the subsequent discovery of three dimensional design rules and optimal design research. This idea can also be used as a reference for other design fields.
- rule extraction /
- propeller design /
- data driven /
- rough set theory /
- Betz condition

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图 1 研究思路

Figure 1. Research ideas

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图 2 动态层次聚类离散与人工离散方法对比

Figure 2. Comparison of dynamic hierarchical clustering discrete and artificial discrete methods

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图 3 动态层次聚类离散结果

Figure 3. Dynamic hierarchical clustering discrete results

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图 4 螺旋桨Ⅱ的离散结果

Figure 4. Discrete results of propeller Ⅱ

下载: 全尺寸图片幻灯片

表 1 螺旋桨主要参数

Table 1. Main parameters of propellers

参数	桨Ⅰ	桨Ⅱ
叶数	4	2
直径/mm	1200	2600
转速/（r/min）	2263	450
速度/（m/s）	55.5	18.5
高度/km	10	12

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表 2 原始决策信息表

Table 2. Original decision information table

论域编号	分散程度（条件属性）	效率（决策属性）
1	0.108	0.7922
2	0.150	0.7904
3	0.123	0.7908
4	0.154	0.7891
5	0.289	0.7756
6	0.341	0.7734
7	0.306	0.7712
8	0.205	0.7877
9	0.280	0.7750
10	0.329	0.7728
11	0.412	0.7685
12	0.404	0.7673
13	0.093	0.7870
14	0.098	0.7858
15	0.131	0.7841
16	0.279	0.7698
17	0.156	0.7844
18	0.155	0.7828
19	0.260	0.7694
20	0.307	0.7673
21	0.353	0.7638
22	0.063	0.7768
23	0.082	0.7809
24	0.113	0.7797
25	0.122	0.7782
26	0.252	0.7639

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表 3 离散结果中的不相容

Table 3. Incompatibility in discrete results

分散程度水平值	效率水平值
1	2
2	1
2	2

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表 4 离散后的决策信息表

Table 4. Discrete decision information table

论域编号	离散后的条件属性		决策属性
论域编号	分散程度水平值	随机数	效率水平值
1	1	20	2
2	1	21	2
3	1	3	2
4	1	26	2
5	2	14	1
6	2	16	1
7	2	10	1
8	1	12	2
9	2	6	1
10	2	18	1
11	2	4	1
12	2	9	1
13	1	24	2
14	1	2	2
15	1	11	2
16	2	7	1
17	1	22	2
18	1	5	2
19	2	1	1
20	2	15	1
21	2	19	1
22	1	8	2
23	1	23	2
24	1	25	2
25	1	17	2
26	2	13	1

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