摘要
为准确高效支持飞机机体损伤的图像化立体化处理,提出一种机体损伤区域的快速划分方法。在分析机体损伤图像特点的基础上,将一维灰度熵划分方法扩展到多维,将滤波函数作为多维灰度函数;由于多维灰度熵划分方法仍存在划分区域混淆和效率低下的明显缺陷,引入细菌觅食优化算法进行改进优化;通过分析细菌觅食的寻优过程,结合多维灰度熵阈值划分方法,提出飞机机体损伤区域快速划分方法。使用该方法对机体损伤图像进行划分实验,实验结果表明,该方法划分图像清晰有效,解决了损伤邻接区域划分混淆的问题,与灰度熵穷举法相比,运算速度有明显提升,能够更好满足飞机智能维修的要求。
To support the airframe damage graphical processing and modeling processing,a rapid division method of airframe damage region was proposed.The characteristics of airframe damage image were analyzed,and on this basis,one-dimension gray entropy division was extended to multi-dimension with filter function as multi-dimension gray function.However,multi-dimension gray entropy division method has obvious defects such as region confusion and low efficiency.Hence,the bacterial foraging optimization algorithm was introduced.The searching optimization process of the bacterial foraging was analyzed,combining with the multi-dimension gray entropy threshold division method,rapid division method of the airframe damage region was proposed.Airframe damage region division experiments using the proposed method were performed.Experimental results show that the divided image is clear and effective.The confusion of damage adjacency region is efficiently solved.Compared with gray entropy exhaustion method,the running speed of the proposed method is improved obviously.It meets the requirement of aircraft intelligent maintenance better.
出处
《计算机工程与设计》
北大核心
2016年第3期737-741,共5页
Computer Engineering and Design
基金
中央高校基本科研业务费专项基金项目(3122014D017)
关键词
机体损伤区域划分
多维灰度熵
细菌觅食优化算法
划分区域混淆
智能维修
airframe damage region division
multi-dimension gray entropy
bacterial foraging optimization algorithm
division region confusion
intelligent maintenance