电焊机2025，Vol.55Issue(6)：118-124,7.DOI:10.7512/j.issn.1001-2303.2025.06.16
大型风电机组叶轮裂纹焊接缺陷图像检测新方法
New Method for Image Detection of Welding Defects in Cracked Impellers of Large Wind Turbines
摘要
Abstract
In response to the low accuracy and efficiency of defect detection in the welding of large wind turbine impeller cracks,an image detection technology based on the particle wavelet mutation algorithm is proposed.Firstly,the original welding defect images are subjected to graying,filtering,and visual enhancement processing to effectively eliminate noise and enhance the features of welding defects.Then,the ROI(Region of Interest)waveform analysis method is used to extract the waveform features within the first-order difference sequence of the welding defects in the image,and further analyze the characteristics of the welding defects.The extracted features are used as inputs to establish an image detection model using machine learning algorithms.The particle wavelet mutation algorithm is used to train and optimize the established model to achieve precise detection of impeller crack welding defect images.Experimental results show that the proposed method can effectively eliminate noise,significantly improve the clarity of welding defect image detection,and achieve high-precision and efficient welding defect detection,providing technical support for the safe operation of wind turbine units.关键词
大型风电机组/叶轮裂纹/焊接缺陷/图像检测/粒子小波变异算法Key words
large wind turbine/impeller cracks/welding defects/image inspection/particle wavelet mutation algorithm分类
金属材料引用本文复制引用
商少波,姚博,周云涛,刘田红..大型风电机组叶轮裂纹焊接缺陷图像检测新方法[J].电焊机,2025,55(6):118-124,7.基金项目
安徽省高校省级自然科学研究项目重点项目(KJ2019A1229) （KJ2019A1229）
