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Defect Detection of the Irregular Turbine Blades Based on Edge Pixel Direction Information

机译:基于边缘像素方向信息的不规则涡轮叶片缺陷检测

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In this paper, we proposed a new method for detecting the defect parts of irregular turbine blades in real-time based on edge pixel direction information. Firstly we detect and track the turbine target with the background subtraction algorithm. And extract possible defective blades in fixed positions of the turbine. Then we split the whole system into two parts: 1) detecting the defect on the left/right terminal of turbine blade, where the well-known statistical HOG feature descriptor is applied to the extracted image corner. The defect blade could be found if its HOG feature is significantly different from that of a normal one; 2) detecting the defect in the middle blade with a new method where the shape changing of the blade edges caused by defect will be determined by applying the least-square method to fit the direction vectors within an adaptive detection window. The experimental results show the effectiveness of the proposed methods. The processing speed is about 11 fps, which basically meets the real-time requirements.
机译:本文提出了一种基于边缘像素方向信息实时检测不规则涡轮叶片缺陷部位的新方法。首先,我们利用背景减除算法检测并跟踪涡轮目标。并在涡轮机的固定位置提取可能存在缺陷的叶片。然后,我们将整个系统分为两部分:1)检测涡轮叶片左/右端子上的缺陷,将众所周知的统计HOG特征描述符应用于提取的图像角。如果缺陷刀片的HOG特征与正常叶片的HOG特征显着不同,则可以发现该缺陷刀片。 2)用一种新方法检测中间叶片中的缺陷,其中将通过应用最小二乘法将方向矢量拟合到自适应检测窗口内来确定由缺陷引起的叶片边缘的形状变化。实验结果表明了所提方法的有效性。处理速度约为11 fps,基本可以满足实时性要求。

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