Commonality Evaluation and Prediction Study of Light and Small Multi-Rotor UAVs

软件可移植性 计算机科学 转子(电动) 钥匙(锁) 领域(数学) 卷积神经网络 人工智能 系统工程 工业工程 工程类 数学 计算机安全 机械工程 程序设计语言 纯数学
作者
Yongjie Zhang,Yongqi Zeng,Kang Cao
出处
期刊:Drones [Multidisciplinary Digital Publishing Institute]
卷期号:7 (12): 698-698 被引量:1
标识
DOI:10.3390/drones7120698
摘要

Light small-sized, multi-rotor UAVs, with their notable advantages of portability, intelligence, and low cost, occupy a significant share in the civilian UAV market. To further reduce the full lifecycle cost of products, shorten development cycles, and increase market share, some manufacturers of these UAVs have adopted a series development strategy based on the concept of commonality in design. However, there is currently a lack of effective methods to quantify the commonality in UAV designs, which is key to guiding commonality design. In view of this, our study innovatively proposes a new UAV commonality evaluation model based on the basic composition of light small-sized multi-rotor UAVs and the theory of design structure matrices. Through cross-evaluations of four models, the model has been confirmed to comprehensively quantify the degree of commonality between models. To achieve commonality prediction in the early stages of multi-rotor UAV design, we constructed a commonality prediction dataset centered around the commonality evaluation model using data from typical light small-sized multi-rotor UAV models. After training this dataset with convolutional neural networks, we successfully developed an effective predictive model for the commonality of new light small-sized multi-rotor UAV models and verified the feasibility and effectiveness of this method through a case application in UAV design. The commonality evaluation and prediction models established in this study not only provide strong decision-making support for the series design and commonality design of UAV products but also offer new perspectives and tools for strategic development in this field.
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