【摘要】 基于线性Radon变换的图像投影方法,改善汽车自动调整臂性能测试仪对分离间隙的提取精度。由于工业领域广泛使用的梯度极值法等传统特征点提取方法对含噪密集的信号非常敏感,很难准确识别在线测试曲线的拐点,降低了曲线特征点的提取精度,增加了误判率。在分离间隙在线测试仪的应用中,基于线性Radon变换法的分离间隙提取技术,能大大改善分离间隙的获取精度和准确度。实验验证,线性Radon变换法的计算误差比梯度极值法的计算误差至少降低10倍,同时,该技术理论研究成果已在杭州沃镭科技有限公司成功推广使用。更多还原

【Abstract】 Here,the linear Radon transformation was applied in a separating clearance on line test system of an automatic brake adjuster to get a separating clearance. The linear Radon transformation was widely used to extract inflection points of an online test system,especially,under noise conditions. Traditional characteristic point extraction methods like the gradient maximum optimal method were widely used in industry areas. Since they were sensitive to signals containing strong noise,those traditional methods are hard to identify the inflection points from online tested curves with signals containing strong noise. Compared with the linear Radon transformation,tradition methods have a much less accuracy of inflection points extraction when applied in a separating clearance online test system of an automatic brake adjuster. The experimental results showed that the computational error of the linear Radon transformation is over 10 times lower than that of the gradient maximum optimal method. The separation clearance extraction technology was successfully used at Hangzhou Wolei tech. Co.,LTD.更多还原