非连续曲面动态测量中异常数据的灰色理论判别法

    Grey Detection and Replacement of Unwanted Asperities in Dynamic Measurement of Discontinuous Curves

    • 摘要: 针对非连续曲面测量中易产生异常数据,数据样本不大等特点,引入一种改良型灰色模型,结合鲁棒性较好的最小一乘法,提出了非连续曲面动态测量中异常数据的灰色理论判别法;给出了全部算式及判别准则,并根据滚刀啮合误差的实测数据进行了验证计算。

       

      Abstract: How to detect and remove unwanted asperities is a critical problem in the dynamic measurement Measurement of discontinuous curves is the dynamic measurement of discrete points,and results frequently in unwanted asperities.Meanwhile,the measurement sample is not big.Based on the features of the grey theory,a modified Grey Model is introduced to approach the measurement data.Combined with the robust minimum deviation principle,a method using grey theory to detect unwanted asperities in the dynamic measurement is studied.All the equations and the distinguishing criterion are given.

       

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