基于图像细化的疲劳断口图像条带周期测量

Fatigue Striation Period Measurement of Fracture Images Based on Image Thinning

研究材料疲劳断裂准确判断测量问题,对材料的疲劳条带周期性进行定量分析疲劳应力和疲劳寿命是测量的一个重要手段,同时准确测量可以得到快修复。针对传统依靠研究人员的经验,采用人工目测,手动计算条带周期时工作量大,效率低的缺点,为了客观、定量、快速的检测疲劳周期,建立了疲劳条带的三角计算模型,并将遗传算法引入图像二值化处理,提出了基于图像细化的周期测量方法。经实际断口图像样本测试表明,采用的方法可以有效的减少人为因素的干予,提高测量精度,能满足断裂故障智能化诊断的要求。

The quantitative analysis for fatigue stress and fatigue life of fatigue striation period is an important means of measurement.At present,the main measurement method of fatigue striation period is based on macroscopic observation and manual calculation,which is a low efficiency work and mainly relying on the experiences of the researchers.In order to study a more objective,quantitativ and high efficiency method of fatigue striation period measuremen,a triangle mathematical model of striation period computing was proposed,and a genetic algorithm was adopted in binary image processing.Then an automatic measurement method based on image thinning was proposed in the paper.The actual experiment results indicate that the proposed method can reduce artificial factors interference and increase the measurement precision,which can satisfy the requirements of intelligent fracture fault diagnosis.