Mechanical properties and microstructures of Al-Li-Cu-Mg-Ag alloy after solution treatments were investigated by means of optical microscopy （OM）, tensile test, hardness measurement and electrical conductivity test,...Mechanical properties and microstructures of Al-Li-Cu-Mg-Ag alloy after solution treatments were investigated by means of optical microscopy （OM）, tensile test, hardness measurement and electrical conductivity test, differential scanning calorimetric （DSC）, energy dispersive X-ray （EDX）, scanning electron microscopy （SEM） and transition electron microscopy （TEM）, respectively The results show that both tensile strength and hardness increase first and then decrease with temperature at constant holding time of 30 min with maximum strength and hardness appearing at 520 ℃. Tensile strength, hardness and elongation of samples treated at 520 ℃ for 30 min are 566 MPa （σb）, 512 MPa （σ0.2）, HB 148 and 8.23% （δ）, respectively. There are certain amount of fine T1 （AI2CuLi） phase dispersing among AI substrates according to TEM images. This may result in mixed fracture morphology with trans-granular and inter-granular delamination cracks observed in SEM images.展开更多
The main methods of the second phase quantitative analysis in current material science researches are manual recognition and extracting by using software such as Image Tool and Nano Measurer. The weaknesses such as hi...The main methods of the second phase quantitative analysis in current material science researches are manual recognition and extracting by using software such as Image Tool and Nano Measurer. The weaknesses such as high labor intensity and low accuracy statistic results exist in these methods. In order to overcome the shortcomings of the current methods, the Ω phase in A1-Cu-Mg-Ag alloy is taken as the research object and an algorithm based on the digital image processing and pattern recognition is proposed and implemented to do the A1 alloy TEM （transmission electron microscope） digital images process and recognize and extract the information of the second phase in the result image automatically. The top-hat transformation of the mathematical morphology, as well as several imaging processing technologies has been used in the proposed algorithm. Thereinto, top-hat transformation is used for elimination of asymmetric illumination and doing Multi-layer filtering to segment Ω phase in the TEM image. The testing results are satisfied, which indicate that the Ω phase with unclear boundary or small size can be recognized by using this method. The omission of these two kinds of Ω phase can be avoided or significantly reduced. More Ω phases would be recognized （growing rate minimum to 2% and maximum to 400% in samples）, accuracy of recognition and statistics results would be greatly improved by using this method. And the manual error can be eliminated. The procedure recognizing and making quantitative analysis of information in this method is automatically completed by the software. It can process one image, including recognition and quantitative analysis in 30 min, but the manual method such as using Image Tool or Nano Measurer need 2 h or more. The labor intensity is effectively reduced and the working efficiency is greatly improved.展开更多
基金Foundation item： Project（6140506） supported by GAD （General Armament Department）, China
文摘Mechanical properties and microstructures of Al-Li-Cu-Mg-Ag alloy after solution treatments were investigated by means of optical microscopy （OM）, tensile test, hardness measurement and electrical conductivity test, differential scanning calorimetric （DSC）, energy dispersive X-ray （EDX）, scanning electron microscopy （SEM） and transition electron microscopy （TEM）, respectively The results show that both tensile strength and hardness increase first and then decrease with temperature at constant holding time of 30 min with maximum strength and hardness appearing at 520 ℃. Tensile strength, hardness and elongation of samples treated at 520 ℃ for 30 min are 566 MPa （σb）, 512 MPa （σ0.2）, HB 148 and 8.23% （δ）, respectively. There are certain amount of fine T1 （AI2CuLi） phase dispersing among AI substrates according to TEM images. This may result in mixed fracture morphology with trans-granular and inter-granular delamination cracks observed in SEM images.
基金Project(51171209)supported by the National Natural Science Foundation of China
文摘The main methods of the second phase quantitative analysis in current material science researches are manual recognition and extracting by using software such as Image Tool and Nano Measurer. The weaknesses such as high labor intensity and low accuracy statistic results exist in these methods. In order to overcome the shortcomings of the current methods, the Ω phase in A1-Cu-Mg-Ag alloy is taken as the research object and an algorithm based on the digital image processing and pattern recognition is proposed and implemented to do the A1 alloy TEM （transmission electron microscope） digital images process and recognize and extract the information of the second phase in the result image automatically. The top-hat transformation of the mathematical morphology, as well as several imaging processing technologies has been used in the proposed algorithm. Thereinto, top-hat transformation is used for elimination of asymmetric illumination and doing Multi-layer filtering to segment Ω phase in the TEM image. The testing results are satisfied, which indicate that the Ω phase with unclear boundary or small size can be recognized by using this method. The omission of these two kinds of Ω phase can be avoided or significantly reduced. More Ω phases would be recognized （growing rate minimum to 2% and maximum to 400% in samples）, accuracy of recognition and statistics results would be greatly improved by using this method. And the manual error can be eliminated. The procedure recognizing and making quantitative analysis of information in this method is automatically completed by the software. It can process one image, including recognition and quantitative analysis in 30 min, but the manual method such as using Image Tool or Nano Measurer need 2 h or more. The labor intensity is effectively reduced and the working efficiency is greatly improved.
