Automatic recognizing for brake shoe key fault of railway freight cars based on image analysis
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摘要: 本文基于数字图像分析技术，提出一种TFDS铁路货车闸瓦插销窜出故障的自动识别方法。算法对原始输入图像进行必要的区域定位、直方图均衡化、去噪等预处理；针对处理后的闸瓦插销的图像，设计适合其形状、纹理和位置3个方面特征的梯度方向直方图来描述闸瓦插销的特征向量；提取特征向量输入到已经训练好的线性可分支持向量机分类器模型中进行故障判断和自动识别。实验数据证明了该识别算法的稳定性、可靠性和实用性。Abstract: This article presented an automatic recognition method to identify the fault of railway truck brake shoe key, based on the technology of digital image analysis of Trouble of moving Freight car Detection System(TFDS). Regional localization for the original image, histogram equalization and image de-noising were taken in image pretreatment.Through the histograms of oriented gradients to extract the feature vector of the brake shoe bolt, the extract features vector was imputed to the trained classifier linearly separable support vector machine (SVM) model for fault diagnosis and automatic recognition. Experimental results demonstrated that the proposed algorithms of automatic fault recognizing for brake shoe key were available, stability and reliability.
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[1] Navneet Dalal, Bill Triggs. Histograms of Oriented Gradients for Human Detection[J]. Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol.2, 2005:886-893. [2] Navneet Dalal. Finding People in Images and Videos[D].Grenoble, France: The French National Institute for Research inComputer Science and Control, 2006: 10-25. [3] Corinna Cortes , V.Vapnik. Support-Vector Networks[J].Machine Learning, 20, 1995:273-297. -
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