基于稀疏表示分类算法的复合绝缘子憎水性检测方法

复合绝缘子表面憎水性的检测是判断其防污闪性能的主要手段之一.本文引入稀疏表示分类算法实现了对复合绝缘子憎水性图像的检测分类.运用最小一范数方法计算稀疏表示系数,通过计算最小残差图像来搜索与测试图像最匹配的训练样本图像,从而准确识别出检测试样的憎水性HC等级.该算法避开了一般模式识别算法中较复杂的特征提取环节,为复合绝缘子憎水性图像识别检测提供了新的思路.实验结果表明,该方法能有效地应用于复合绝缘子憎水性图像的分级.

Composite Insulator's Hydrophobicity Detection Method Based on Sparse Representation Classification Algorithm

The composite insulator surface hydrophobicity detection is one of the primary means to determine its anti flashover performance. This paper introduces the sparse representation classification algorithm to classify composite insulator's hydrophobic image. It uses the smallest normal method to calculate the coefficient of sparse representation and searches the training sample image that best matches the test image by calculating the minimum residual image, therefore the test image's hydrophobic HC level is accurately identified. The algorithm has successfully avoided complicated feature extraction in general pattern recognition algorithms, thus providing a new way for composite insulator's hydrophobic image recognition and detection. The experimental results show that the method can be effectively applied in the composite insulator's hydrophobic image classification.