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浙江大学学报(工学版)
浙江大学学报(工学版)  2022, Vol. 56 Issue (8): 1568-1577    DOI: 10.3785/j.issn.1008-973X.2022.08.011
机械与能源工程     
基于犹豫模糊集的飞机驾驶舱形态评价
陈彦蒿(),余隋怀,初建杰*(),寸文哲
西北工业大学 工业设计与人机工效工信部重点实验室，陕西 西安 710072
Evaluation of aircraft cockpit form based on hesitant fuzzy sets
Yan-hao CHEN(),Sui-huai YU,Jian-jie CHU*(),Wen-zhe CUN
Key Laboratory of Industrial Design and Ergonomics, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi’an 710072, China
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摘要：

为了解决飞机驾驶舱形态设计过程中，飞行员存在的认知偏好描述困难及决策犹豫的问题，提出基于犹豫模糊集的飞机驾驶舱设计形态综合评价方法. 通过对驾驶舱设计形态的认知需求分析，建立了驾驶舱设计形态认知需求的属性特征体系；利用粗数评价模型得到影响驾驶舱设计形态认知偏好的评价指标，提取驾驶舱关键部件设计形态特征线，获取了驾驶舱关键部件设计形态的核心特征，进一步结合驾驶舱设计形态的认知偏好评价指标，获取综合决策评价值；采用认知熵理论修正评价指标权重，构建集结犹豫模糊评价模型，从而得到复合认知偏好下的驾驶舱设计形态优先级排序. 与5种同类评价算法进行比较及一致性检验，结果表明本研究所提方法具有良好的可靠性且能有效解决评价信息的犹豫性，能够较好地实现对飞机驾驶舱设计形态认知偏好的精确评估.
关键词： 飞机驾驶舱形态;  认知需求;  认知偏好;  犹豫模糊集;  综合评价    
Abstract:

A comprehensive evaluation method of aircraft cockpit design form based on hesitant fuzzy set was proposed, in order to solve the problems of difficult description of cognitive preferences and hesitation in decision making of pilots in the process of aircraft cockpit form design. The attribute feature system of the cognitive demand of cockpit design form was established by analyzing the cognitive demand of cockpit design form. The evaluation indexes affecting the cognitive preference of cockpit design form were obtained by using the rough number evaluation model, the features lines of cockpit key component design form were extracted, the core features of cockpit key component design form were obtained, and further combined with the cognitive preference evaluation index of cockpit design form, the comprehensive decision evaluation value was obtained. The cognitive entropy theory was used to modify the evaluation index weights and construct the set hesitant fuzzy evaluation model, so as to obtain the cockpit design form priority ranking under compound cognitive preference. Results show that the proposed method has good reliability and can effectively solve the hesitation of evaluation information, which can better achieve the accurate evaluation of the cognitive preference of aircraft cockpit design form.
Key words: aircraft cockpit form    cognitive demand    cognitive preference    hesitant fuzzy set    comprehensive evaluation
收稿日期: 2021-06-12 出版日期: 2022-08-30
CLC:  TB 47  
基金资助: 国防科技基础加强计划技术领域基金资助项目(2020-JCJQ-JJ-439)；高等学校学科创新引智计划资助项目(B13044)
通讯作者: 初建杰     E-mail: chenyhmail@163.com;cjj@nwpu.edu.cn
作者简介: 陈彦蒿（1990—），男，博士生，从事认知工效研究. orcid.org/0000-0003-2755-6036. E-mail: chenyhmail@163.com
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引用本文:

陈彦蒿,余隋怀,初建杰,寸文哲. 基于犹豫模糊集的飞机驾驶舱形态评价[J]. 浙江大学学报(工学版), 2022, 56(8): 1568-1577.

Yan-hao CHEN,Sui-huai YU,Jian-jie CHU,Wen-zhe CUN. Evaluation of aircraft cockpit form based on hesitant fuzzy sets. Journal of ZheJiang University (Engineering Science), 2022, 56(8): 1568-1577.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2022.08.011    或    https://www.zjujournals.com/eng/CN/Y2022/V56/I8/1568

图 1  认知需求的属性特征层级结构
需求类型 属性特征 特征定义
本能需求 安全防护感 驾驶舱形态具备安全可靠和基础保障
操纵空间感 驾驶舱形态操纵空间在肢体可达域范围
轮廓间距感 驾驶舱形态设计元件接口间距合理
总体布局感 驾驶舱形态机载系统设施布置准确
感官需求 部件协调感 驾驶舱形态部件，定位协调舒适
符号统一感 驾驶舱形态符号整体清晰统一
标识易读感 驾驶舱形态元素能够准确辨识
区域比例感 驾驶舱形态部件尺寸比例恰当
整体对称感 驾驶舱形态整体对称美观
感性需求 简洁感 驾驶舱形态简洁规整
科技感 驾驶舱形态创新集成
精密感 驾驶舱形态精准周密
智能感 驾驶舱形态感知决策
现代感 驾驶舱形态前瞻开放
表 1  驾驶舱设计形态认知需求的属性特征
图 2  驾驶舱设计形态认知偏好评价指标确定
图 3  犹豫模糊综合评价模型
图 4  驾驶舱形态评价方案库
特征属性A 分值
D1 D2 D3 … D15 D16
A1 3 7 9 … 7 5
A2 1 5 5 … 5 3
A3 1 3 5 … 3 3
A4 3 5 7 … 7 5
$\vdots $ $\vdots $ $\vdots $ $\vdots $ $\vdots $ $\vdots $
A13 7 7 9 … 5 7
A14 3 5 5 … 5 3
表 2  驾驶舱形态设计认知需求的属性特征评价结果
本能需求 属性 D1 D2 D3 … D15 D16 均值
A1 粗数 [3.0,5.5] [5.3,7.3] [5.5,9.0] … [5.3,7.3] [4.1,6.3] [4.4,6.6]
边界 2.5 2.0 3.5 2.0 2.2 2.2
A2 粗数 [1.0,3.4] [3.1,5.3] [3.1,5.3] … [3.1,5.3] [2.2,4.2] [2.3,4.5]
边界 2.4 2.2 2.2 2.2 2.0 2.2
A3 粗数 [1.0,3.0] [2.2,3.9] [2.7,5.5] … [2.2,3.9] [2.2,3.9] [2.0,4.1]
边界 2.0 1.7 2.8 1.7 1.7 2.1
A4 粗数 [3.0,5.4] [4.2,6.2] [5.1,7.3] … [5.1,7.3] [4.2,6.2] [4.3,6.5]
边界 2.4 2.0 2.2 2.2 2.0 2.2
表 3  驾驶舱设计形态的本能需求属性特征粗数
感官需求 属性 D1 D2 D3 … D15 D16 均值
A5 粗数 [4.5,5.8] [5.3,7.0] [5.3,7.0] … [5.3,7.0] [4.5,5.8] [4.5,6.1]
边界 1.3 1.7 1.7 1.7 1.3 1.6
A6 粗数 [2.3,4.0] [3.0,5.4] [3.3,7.0] … [2.3,4.0] [2.3,4.0] [2.2,4.4]
边界 1.7 2.4 3.7 1.7 1.7 2.2
A7 粗数 [1.0,3.1] [2.5,3.6] [3.1,5.0] … [2.5,3.6] [2.5,3.6] [2.4,3.9]
边界 2.1 1.1 1.9 1.1 1.1 1.5
A8 粗数 [4.6,6.0] [5.4,7.3] [5.4,7.3] … [4.6,6.0] [4.6,6.0] [4.7,6.5]
边界 1.4 1.9 1.9 1.4 1.4 1.8
A9 粗数 [2.2,3.7] [2.2,3.7] [2.9,5.0] … [2.2,3.7] [2.2,3.7] [2.0,3.8]
边界 1.5 1.5 2.1 1.5 1.5 1.8
表 4  驾驶舱设计形态的感官需求属性特征粗数
感性需求 D1 D2 D3 … D15 D16 均值
A10 粗数 [2.4,3.9] [3.4,5.0] [3.4,5.0] … [3.4,5.0] [1,3.4.0] [2.5,4.2]
边界 1.5 1.6 1.6 1.6 2.4 1.7
A11 粗数 [5.4,9.0] [4.5,5.9] [4.5,5.9] … [4.9,8.0] [4.5,5.9] [4.4,6.5]
边界 3.6 1.4 1.4 3.1 1.4 2.1
A12 粗数 [2.3,4.4] [3.3,5.6] [3.8,7.0] … [3.3,5.6] [2.3,4.4] [2.6,5.0]
边界 2.1 2.3 3.2 2.3 2.1 2.4
A13 粗数 [5.9,7.7] [5.9,7.7] [6.5,9.0] … [5.0,6.5] [5.9,7.7] [5.6,7.4]
边界 1.8 1.8 2.5 1.5 1.8 1.8
A14 粗数 [2.8,3.9] [3.5,5.3] [3.5,5.3] … [3.5,5.3] [2.8,3.9] [3.0,4.5]
边界 1.1 1.8 1.8 1.8 1.1 1.5
表 5  驾驶舱设计形态的感性需求属性特征粗数
图 5  粗数下边界与粗边界结果
图 6  模糊评价术语集程度表
方案U A1 A4 A5 A8 A11 A12
u1 {0.38, 0.44, 0.53} {0.56, 0.63, 0.68} {0.38, 0.45, 0.52} {0.17, 0.20, 0.29} {0.33, 0.38, 0.47} {0.23, 0.28, 0.37}
u2 {0.47, 0.55, 0.60} {0.43, 0.49, 0.56} {0.25, 0.30, 0.38} {0.32, 0.37, 0.47} {0.18, 0.25, 0.35} {0.18, 0.23, 0.33}
u3 {0.17, 0.20, 0.28} {0.17, 0.21, 0.28} {0.22, 0.27, 0.36} {0.20, 0.25, 0.33} {0.16, 0.20, 0.28} {0.44, 0.48, 0.55}
u4 {0.18, 0.22, 0.31} {0.38, 0.48, 0.56} {0.36, 0.41, 0.49} {0.25, 0.30, 0.40} {0.34, 0.41, 0.49} {0.17, 0.22, 0.32}
$\vdots $ $\vdots $ $\vdots $ $\vdots $ $\vdots $ $\vdots $ $\vdots $
u29 {0.53, 0.62, 0.66} {0.52, 0.59, 0.65} {0.60, 0.68, 0.74} {0.67, 0.76, 0.80} {0.63, 0.72, 0.76} {0.63, 0.71, 0.77}
u30 {0.66, 0.73, 0.77} {0.65, 0.74, 0.78} {0.64, 0.73, 0.78} {0.55, 0.65, 0.70} {0.53, 0.61, 0.67} {0.46, 0.53, 0.59}
表 6  犹豫模糊决策矩阵
方案 s+ s? si
u1 0.83 0.95 0.54
u2 0.80 0.97 0.55
u3 0.72 0.99 0.58
u4 0.80 0.98 0.55
$\vdots $ $\vdots $ $\vdots $ $\vdots $
u29 0.98 0.80 0.45
u30 0.97 0.82 0.46
表 7  评价方案综合相似度结果
图 7  评价方案优劣分布
模型 Nc
u1 u2 u3 u4 $ \cdots $ u29 u30
灰色关联法 23 26 30 28 $ \cdots $ 4 5
TOPSIS 23 26 30 28 $ \cdots $ 4 5
熵权TOPSIS 21 26 30 27 $ \cdots $ 4 5
RSR 24 27 30 28 $ \cdots $ 4 5
VIKOR 27 25 30 28 $ \cdots $ 3 5
表 8  不同评价模型排序结果
图 8  各类评价排序的散点分布
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