锻压技术

用于Q235低碳钢的数字图像相关法应变检测

英文标题：Strain detection by digital image correlation method on Q235 low carbon steel

单位：1.郑州轻工业大学机电工程学院 2.三峡大学水电机械设备设计与维护湖北省重点实验室

分类号：

出版年,卷(期):页码：2022,47(3):182-190

摘要：

为解决传统应变检测方法中存在的测量结果精度低、容易改变试样的力学性能、无法实现全场变形测量等问题,采用数字图像相关法对Q235低碳钢的力学性能进行研究，将拉伸试验结果与ABAQUS数值模拟结果进行对比分析，通过引入差值系数来研判各力学参数模拟结果的精度。结果表明：模拟所得应变分布数值与数字图像相关法所得结果吻合较好，且最大主应变值的吻合度最高；屈服强度和抗拉强度的差值系数均小于1.000%，且抗拉强度的差值系数最小，为0.011%；伸长率和断面收缩率的差值系数较大，其中伸长率的差值系数最大，为2.054%。对比结果表明：数字图像相关法应用于Q235低碳钢的变形及应变的测量是真实有效的，同时，该方法为其他材料的变形测量提供了借鉴。

In order to solve the problems existing in traditional strain detection method， such as low accuracy of measurement results, easy to change the mechanical properties of samples, and inability to realize full-field deformation measurement, the mechanical properties of Q235 low carbon steel were studied by digital image correlation method. Then, the tensile test results were compared and analyzed with the numerical simulation results of ABAQUS, and the accuracy of simulation results for various mechanical parameters was evaluated by introducing the difference coefficient. The results show that the strain distribution values obtained by the simulation are in good agreement with those obtained by the digital image correlation method, and the maximum principal strain values have the highest agreement. The difference coefficients of yield strength and tensile strength are all less than 1.000%, and the difference coefficient of tensile strength is the smallest, which is 0.011%, the differences coefficients of elongation and area reduction are larger, and the difference coefficient of elongation is the biggest, which is 2.054%. The comparison results show that the digital image correlation method is really effective in the deformation and strain measurement of Q235 low carbon steel, which provides a reference for the deformation measurement of other materials.

基金项目：

国家自然科学基金面上项目（51975324）；2020年度河南省高校科技创新团队（20IRTSTHN015）；江苏省盐城市“515”创新领军人才项目（盐委[2020]40号）；河南省科技攻关项目（202102210087）；郑州市科技局产学研项目（郑科函[2020]3号）

张德海（1973-），男，博士，教授 E-mail：dhzhang@zzuli.edu.cn

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