航空发动机钛合金压气机叶片工作时,由于长时间高强度服役和异物损伤,叶片会发生变形、凹痕、磨损、裂纹甚至断裂.激光熔覆技术因其热影响区小、沉积性能好、成形精度和自动化程度高,已经成为叶片修复的重要方法之一.熔池几何特征是影响熔覆质量的关键因素,因此本文针对熔池实时监测,提出了一种基于图像处理的识别测量算法.首先,通过图像掩膜提取ROI区域,再对ROI区域进行伽马变换、阈值二值化实现熔池区域的分割;然后计算轮廓面积特征进行去噪;最后采用AABB包围盒对熔池的几何特征进行提取,实现了熔覆过程中熔池长宽的实时监测.最终通过多参数正交试验,验证算法平均识别误差为0.24 mm.
Abstract
When the titanium alloy compressor blade of the aircraft engine works,due to the long period of high-strength service and foreign body damage,the blade will deform,dent,wear,crack and even break.Laser cladding technology has become one of the important methods of blade repair due to its small heat affected zone,good deposition performance,high forming accuracy and high degree of automation.The geometric characteristics of the melt pool are the key factors affecting the quality of the cladding,so this paper proposes an identification measurement algorithm based on image processing for the real-time monitoring of the melt pool.First of all,the ROI region is extracted by the image mask,and then the gamma transform is performed on ROI region,the threshold bination is valued to realize the segmentation of the melt pool area,the contour area feature is calculated for denoising,and finally the AABB enveloping box is used to extract the geometric characteristics of the molten pool,which realizes the real-time monitoring of the length and width of the molten pool during the cladding process.Finally,through the multi-parameter orthogonal experiment,the average recognition error of the verification algorithm is 0.24 mm.
关键词
TC17钛合金/激光熔覆/熔池监视/图像处理/工艺参数
Key words
TC17 titanium alloy/Laser cladding/Molten pool monitoring/Image processing/Process parameters
维普
万方数据