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Analysis of single flank test results providing topography errors of spiral bevel gears

机译:单侧翼试验结果分析螺旋锥齿轮的形貌误差

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A method for analyzing single flank test results is proposed. The analysis yields geometrical deviations of spiral bevel gears. It is based on extracting information on the meshing tooth surfaces from the transmission error curve and digital photograph of the contact pattern. A neural network is trained by a batch of computer simulated transmission error curves and respective contact patterns belonging to systematically varied geometrical deviations. Taking advantage of the generalization capability of the neural network, it can be used to yield tooth flank topography errors on the basis of single flank test measuring results. Giving similar results to coordinate measurement, the method extends the capabilities of single flank test significantly. It saves costly coordinate measuring time, which may be especially advantageous in case of large bevel gears. It takes only minor changes for the analysis to be applicable for any types of gears.
机译:提出了一种分析单个侧翼测试结果的方法。分析产生螺旋锥齿轮的几何偏差。它基于从透射误差曲线和接触图案的数字照片提取关于啮合齿表面的信息。通过一批计算机模拟传输错误曲线以及属于系统变化的几何偏差的相应接触模式训练了神经网络。利用神经网络的泛化能力,可用于基于单个侧翼测试测量结果屈服的牙齿形状误差。对坐标测量提供类似的结果,该方法显着延伸了单个侧翼测试的能力。它可以节省昂贵的坐标测量时间,这在大锥齿轮的情况下可能是特别有利的。对分析仅适用于任何类型的齿轮只有微小的变化。

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