This paper studies on a division method of the whole aeroengine loading spectrum flight mission segment and rotor speed mission segment,which is based on the actual flight actions and related to the flight operations ...This paper studies on a division method of the whole aeroengine loading spectrum flight mission segment and rotor speed mission segment,which is based on the actual flight actions and related to the flight operations of aeroengine and is suitable for the variable-speed aeroengines such as turbojet and turbofan.Through the research,the aeroengine loading spectrum operation-related mission segments can be divided,which can provide important data basis for the life research on the structures which are sensitive to flight maneuver(such as the main shaft,large gearbox and installation section),lay a foundation for the simulation,compilation and prediction of the whole aeroengine loading spectrum.Firstly,based on the summary of basic flight actions in actual flight,the division of flight mission segment was realized by programming.Moreover,the aeroengine rotor speed mission segments,associated with flight actions and missions,were divided based on the flight mission segment division results.Besides,the efficiency and accuracy of the mission segment division results were verified by adopting measured loading spectrum data.Finally,the characteristics of speed mission segment division results were compared and analyzed in tables and figures.The comparison results show that the characteristics of similar speed mission segments are similar,while the characteristics of different speed mission segments are different.And the shapes of similar mission segments vary to the change of flight actions and operations,which can reflect the operation-related feature of the segments.展开更多
为解决超声渡越衍射时差(Time of flight diffraction,TOFD)检测图像中缺陷识别的问题,分析检测图像的特点,研究图像自动分割的算法,其中包括图像预处理及图像分割。提出基于信号互相关算法的图像预处理方法,在此基础上,应用峰值搜索方...为解决超声渡越衍射时差(Time of flight diffraction,TOFD)检测图像中缺陷识别的问题,分析检测图像的特点,研究图像自动分割的算法,其中包括图像预处理及图像分割。提出基于信号互相关算法的图像预处理方法,在此基础上,应用峰值搜索方法提取焊缝区域,利用带控制标记符的分水岭变换对预处理的图像进行分割,从而识别出缺陷目标。利用提出的图像自动分割方法分割不同的超声TOFD检测图像。研究表明,基于信号互相关算法的图像校正方法在一定程度上可抑制检测图像的畸变,焊缝区域图像的提取可减少图像分割过程的计算量,从局部极值的角度出发的带控制标记符的分水岭变换实现缺陷目标的分割。与基于阈值方法的图像分割结果相比,图像自动分割算法较好地解决了近表面缺陷的识别问题,同时提出的方法也可用于含多个缺陷的图像分割。展开更多
基金co-supported by the Foundation of graduate innovation base of Nanjing University of Aeronautics and Astronautics,China(Nos.kfjj20190206 and kfjj20200218)the National Science and Technology Major Project,China(No.J2019-V0009-0103)。
文摘This paper studies on a division method of the whole aeroengine loading spectrum flight mission segment and rotor speed mission segment,which is based on the actual flight actions and related to the flight operations of aeroengine and is suitable for the variable-speed aeroengines such as turbojet and turbofan.Through the research,the aeroengine loading spectrum operation-related mission segments can be divided,which can provide important data basis for the life research on the structures which are sensitive to flight maneuver(such as the main shaft,large gearbox and installation section),lay a foundation for the simulation,compilation and prediction of the whole aeroengine loading spectrum.Firstly,based on the summary of basic flight actions in actual flight,the division of flight mission segment was realized by programming.Moreover,the aeroengine rotor speed mission segments,associated with flight actions and missions,were divided based on the flight mission segment division results.Besides,the efficiency and accuracy of the mission segment division results were verified by adopting measured loading spectrum data.Finally,the characteristics of speed mission segment division results were compared and analyzed in tables and figures.The comparison results show that the characteristics of similar speed mission segments are similar,while the characteristics of different speed mission segments are different.And the shapes of similar mission segments vary to the change of flight actions and operations,which can reflect the operation-related feature of the segments.
文摘为解决超声渡越衍射时差(Time of flight diffraction,TOFD)检测图像中缺陷识别的问题,分析检测图像的特点,研究图像自动分割的算法,其中包括图像预处理及图像分割。提出基于信号互相关算法的图像预处理方法,在此基础上,应用峰值搜索方法提取焊缝区域,利用带控制标记符的分水岭变换对预处理的图像进行分割,从而识别出缺陷目标。利用提出的图像自动分割方法分割不同的超声TOFD检测图像。研究表明,基于信号互相关算法的图像校正方法在一定程度上可抑制检测图像的畸变,焊缝区域图像的提取可减少图像分割过程的计算量,从局部极值的角度出发的带控制标记符的分水岭变换实现缺陷目标的分割。与基于阈值方法的图像分割结果相比,图像自动分割算法较好地解决了近表面缺陷的识别问题,同时提出的方法也可用于含多个缺陷的图像分割。
