Sun Kai. Research on Blade Icing Detection Method Based on Image Recognition[J]. 2019, 42(2): 1-5.DOI:
基于图像识别的叶片结冰检测方法研究
摘要
随着化石燃料的大量消耗
环境污染严重
清洁、环保的可再生能源发电渗透率持续提升
寒冷地区风电场建设规模不断扩大
将导致叶片结冰
严重会导致叶片断裂
因此有必要对叶片结冰识别进行深入研究。通过分析现有的叶片结冰检测方法
基于图像识别
通过改进Canny算法与显著物识别算法结合
将图像的边缘像素识别出来
然后计算每一个点的像素梯度
利用灰度值分割法确定最优阈值
再进行显著物的识别
对叶片结冰图像识别进行研究。研究表明叶片结冰图像识别高效可靠
可以有助于对叶片进行除冰
确保风电机组安全可靠的运行。
Abstract
With the consumption of fossil fuels,environmental pollution is serious,the permeability of clean and environmental protection renewable energy power generation continues to increase. And with the expansion of wind farm construction in cold areas,it will lead to blade icing,which will seriously lead to blade breakage. Therefore,it is necessary to study the blade icing recognition. Based on the analysis of the existing blade icing detection methods,the edge pixels of the image are recognized by combining the improved Canny algorithm with the salient recognition algorithm,and the pixel gradient of each point is calculated. The optimal threshold is determined by using gray value segmentation method,and after the significant recognition is carried out,the recognition of icing image of the blade is studied. The research shows that the image recognition of blade icing has a high efficiency and reliability,which can help the blade deicing and ensure the safe and reliable operation of wind turbines.