Multi-dimensional and Multi-threshold Airframe Damage Region Division Method Based on Correlation Optimization

基于关联优化的多维多阈值机体损伤区域划分

In order to obtain the image of airframe damage region and provide the input data for aircraft intelligent maintenance,a multi-dimensional and multi-threshold airframe damage region division method based on correlation optimization is proposed.On the basis of airframe damage feature analysis,the multi-dimensional feature entropy is defined to realize the full fusion of multiple feature information of the image,and the division method is extended to multi-threshold to refine the damage division and reduce the impact of the damage adjacent region’s morphological changes on the division.Through the correlation parameter optimization algorithm,the problem of low efficiency of multi-dimensional multi-threshold division method is solved.Finally,the proposed method is compared and verified by instances of airframe damage image.The results show that compared with the traditional threshold division method,the damage region divided by the proposed method is complete and accurate,and the boundary is clear and coherent,which can effectively reduce the interference of many factors such as uneven luminance,chromaticity deviation,dirt attachment,image compression,and so on.The correlation optimization algorithm has high efficiency and stable convergence,and can meet the requirements of aircraft intelligent maintenance.

为了快速获取机体损伤区域图像,为飞机智能维修提供数据输入,提出了一种基于关联优化的多维多阈值机体损伤区域划分方法。在机体损伤特征分析的基础上,定义了多维特征熵以充分融合损伤图像多样化特征信息。通过设计多阈值损伤区域划分方法,细化了损伤区域,减少了损伤邻域形态变化对划分效果的影响。使用关联参数优化算法解决了多维多阈值划分方法效率低下的问题。最后,以机身损伤图像为例,对该方法进行了对比和验证。结果表明,与传统的阈值划分方法相比,该方法划分的损伤区域准确完整、边界清晰,可以有效地减少亮度不均匀、色度偏差、污垢附着及图像压缩等诸多因素的干扰。关联优化算法效率高且收敛稳定,能够满足飞机智能维修的要求。