The GaAs material is a major semiconductor material,and it has high electron transfer rate and direct transition energy band structure.The devices and integrated circuits fabricated on the GaAs substrates have a lot o...The GaAs material is a major semiconductor material,and it has high electron transfer rate and direct transition energy band structure.The devices and integrated circuits fabricated on the GaAs substrates have a lot of advantages such as high speed information processing.Small perturbations in the manufacturing of GaAs materials can lead to defects.The defects in the GaAs materials can degrade the performance of materials.A new method is presented in this paper for detecting the micro-defects in GaAs materials by using time resolved emissions.In this method,the micro-defects in GaAs materials are detected by making use of the photon emission features of microdefects.The strength of the emitted photons from the micro-defects is increased by applying the electric current or the periodic pulse signals to GaAs materials.The singlephoton detector is used to detect the photon emissions of the micro-defects.The time resolved photon emissions and single-photon detection are used to record and compare the amounts of the emitted photons that come from the given regions of the normal GaAs materials and the defective GaAs materials.A lot of experimental results show that the micro-defects in the GaAs materials can be detected by using the method proposed in this paper.展开更多
针对球栅阵列封装(BGA)焊盘的高密度性问题,以Visual Studio 2013和Open CV机器视觉库为开发平台,设计了一套球栅阵列封装焊盘缺陷视觉检测方案。通过工业相机在红色环形光源下采集PCB裸板图像,选取图像预处理后的合格PCB裸板图像作为模...针对球栅阵列封装(BGA)焊盘的高密度性问题,以Visual Studio 2013和Open CV机器视觉库为开发平台,设计了一套球栅阵列封装焊盘缺陷视觉检测方案。通过工业相机在红色环形光源下采集PCB裸板图像,选取图像预处理后的合格PCB裸板图像作为模板;采集待测PCB裸板图像,进行预处理,采用基于金字塔匹配方法进行图像配准,分割BGA焊盘区域;通过几何法检测焊盘大小和形状,运用图像差分法检测焊盘是否缺失或粘连。实验结果表明,该方案可以正确识别各类缺陷类型,不仅便于对缺陷类型统计分析,而且在检测速度以及可靠性方面具有较好的效果。展开更多
基金supported by the National Natural Science Foundation of China (61072028)the Project of Department of Education of Guangdong Province (2012KJCX0040)Guangdong Province and Chinese Ministry of Education Cooperation Project of Industry,Education and Academy (2009B090300339)
文摘The GaAs material is a major semiconductor material,and it has high electron transfer rate and direct transition energy band structure.The devices and integrated circuits fabricated on the GaAs substrates have a lot of advantages such as high speed information processing.Small perturbations in the manufacturing of GaAs materials can lead to defects.The defects in the GaAs materials can degrade the performance of materials.A new method is presented in this paper for detecting the micro-defects in GaAs materials by using time resolved emissions.In this method,the micro-defects in GaAs materials are detected by making use of the photon emission features of microdefects.The strength of the emitted photons from the micro-defects is increased by applying the electric current or the periodic pulse signals to GaAs materials.The singlephoton detector is used to detect the photon emissions of the micro-defects.The time resolved photon emissions and single-photon detection are used to record and compare the amounts of the emitted photons that come from the given regions of the normal GaAs materials and the defective GaAs materials.A lot of experimental results show that the micro-defects in the GaAs materials can be detected by using the method proposed in this paper.
文摘针对球栅阵列封装(BGA)焊盘的高密度性问题,以Visual Studio 2013和Open CV机器视觉库为开发平台,设计了一套球栅阵列封装焊盘缺陷视觉检测方案。通过工业相机在红色环形光源下采集PCB裸板图像,选取图像预处理后的合格PCB裸板图像作为模板;采集待测PCB裸板图像,进行预处理,采用基于金字塔匹配方法进行图像配准,分割BGA焊盘区域;通过几何法检测焊盘大小和形状,运用图像差分法检测焊盘是否缺失或粘连。实验结果表明,该方案可以正确识别各类缺陷类型,不仅便于对缺陷类型统计分析,而且在检测速度以及可靠性方面具有较好的效果。
