水稻茎秆力学性能的准确描述是水稻抗倒伏力学分析的关键。由于茎秆是由生物活性材料组成的形状不规则柔性结构,传统的测试方法难以对其力学性能进行准确测量。以南方水稻为研究对象,采用拉伸试验机对水稻茎秆进行了拉伸试验。首先采用传统的应变片方法测量应变,继而探索采用图像分析法实现非接触、高精度地测量水稻茎秆的截面尺寸、拉伸变形。用数字摄像机记录不同荷载水平下试件表面的数字图像,采用数字图像相关分析法(DIC)进行分析,通过两种方法计算茎秆的轴向应变;将完成拉伸实验的试件切片,采集其横截面的数字图像,通过数字图像分析技术得到其几何特性,并对大量实验数据进行了统计分析,实现了对水稻茎秆弹性模量、抗弯刚度等的合理描述。实验结果表明,采用传统的应变片测量求得的水稻茎秆的弹性模量的离散性极大,超出样本差异性的范围,而采用数字图像分析方法得到的弹性模量、抗弯刚度的结果有一定的离散性,但分布比较合理,比较准确地反映了水稻茎秆相关的力学性能。
Accurate description of paddy stem's mechanical properties is a key factor for paddy's lodging resistance analysis.It's hard to accurately measure the mechanical properties of paddy's stems by traditional measurement due to its heterogeneous living biomaterial component with soft irregular cross section structure.In author's investigation,tensile tests were carried for paddy stem of a kind of rice growing in South China.Firstly,tensile strains were measured by using traditional strain gauges;then,image analysis method was adopted to accomplish non-contact measurement of stem's cross section dimension and tensile deformation with high accuracy.Specimen's surface digital images under different loading levels during tensile process were recorded by a digital camera,and were analyzed by using Digital Image Correlation(DIC) method.Stem's axial strain was calculated by above two different methods.The cross section's digital images were collected for tested specimen's slice to obtain their geometric properties by digital image analysis.Statistical analysis was carried out for a large quantity of experimental data.Finally,the reasonable description for paddy stem's elastic modules and flexural rigidity was achieved.Experimental results show that elastic modulus dispersion by means of strain gauge measurement presents large discreteness beyond the scope of the sample differences;although the distribution of elastic modulus and flexural rigidity obtained by method of DIC also presents certain discreteness,but has a reasonable distribution.Comparatively,the latter correctly describe the mechanical properties of paddy stem.