基于机器视觉技术的飞机绕机外观检查方法研究
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    摘要:

    大型民用飞机试飞和航线运营期间,对其外观表面进行绕机外观检查是适航性安全检查的必要工作。目前飞机的绕机检查主要采用人工绕机方式,该方式,且成本高、效率低,易出现漏检、误检等人为因素,因此智能外观表面检查方法的研究是一项迫切的任务。相比于其他工业检测任务,飞机外观检查智能识别目前无公开数据集,且飞机真实外观损伤类型多样。通过对飞机外观图像的采集和处理,研究基于YOLO V3的飞机表面检查工程方法,初步建立了飞机外观损伤图像数据集框架。首先采用YOLO检测网络粗略获取飞机外观损伤位置和损伤类型,其次针对不同损伤类型的特点,用水平集算法获取图像块中更精准的损伤位置,最后根据精细化后的结果进行量化分析。提出了能够解决机器深度学习网络智能检测已知类别损伤的方法,对未知损伤具有较强容忍度和较大的灵活性与适应性。实践表明,本文提出的方法可以解决传统人工目视检测的部分弊端,可以为机器人智能绕机检查的工程应用提供技术参考,对降低飞机试飞和运营阶段的维修、维护成本有重要意义。

    Abstract:

    During the flight test and route operation of large civil aircraft, it is necessary to inspect the appearance of the aircraft for damage around the aircraft. At present, the aircraft around inspection mainly adopts manual winding method, which has high cost and low efficiency, and is prone to human factors such as missed detection and misdetection. Therefore, the research on intelligent surface inspection method is an urgent task. Compared with other industrial detection tasks, this project currently has no public data set, and the real appearance surface image is blurred and diversified. In this paper, an aircraft surface damage image data set is preliminarily established, and an aircraft surface inspection engineering method based on YOLO V3 is proposed. The framework can solve the common deep learning network intelligent detection or recognition of known types of damage, has a strong tolerance to the unknown damage, making the algorithm has greater flexibility and adaptability. Firstly, the YOLO detection network was used to roughly obtain the damage location and damage classification of aircraft appearance. Secondly, according to the characteristics of different damage types, the appropriate traditional algorithm was used to obtain the more accurate damage location in the image block. Finally, the quantitative analysis was carried out according to the refined results. A method is proposed to solve the problem of intelligent detection of known category damage by machine deep learning network, which has strong tolerance and flexibility and adaptability to unknown damage. The experiment and practice show that the algorithm proposed in this paper can overcome the disadvantages of the traditional manual visual inspection, reduce the maintenance and maintenance cost of aircraft during flight test and operation, and is of great significance to the maintainability design of aircraft.

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李喜柱,陈智超,汪顺利,等.基于机器视觉技术的飞机绕机外观检查方法研究[J].民用飞机设计与研 究,2021(2):18-24LI Xizhu, CHEN Zhichao, WANG Shunli, et al.[J]. Civil Aircraft Design and Research,2021,(2):18-24. ( in Chinese)

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  • 在线发布日期: 2021-07-08
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