Optics and Precision Engineering, Volume. 23, Issue 11, 3192(2015)

Evaluation of gear errors based on orthogonal distance regression gear profile

LIN Hu1,*... SHI Zhao-yao2, XUE Zi1 and YANG Guo-liang1 |Show fewer author(s)
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  • 2[in Chinese]
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    To obtain the error of gear characterized curves from gear topographic inspection, a method of gear profile orthogonal distance regression was proposed. Some algorithms involved in the method were researched, such as the matching of a real gear profile with a theoretical gear profile, the calculation and decomposition of topographic error and the evaluation of profile character line error. Firstly, topographic points were obtained by coordinate measurement, and the nonlinear equation including parameters of theoretic profile was established. Then, the nonlinear equation was solved to get the optimal parameters of the regression gear profile and to obtain the theoretical gear profile matching with the real gear profile. Here, the orthogonal distances from measuring points to the theoretical gear surface were calculated as the topographic errors. Finally, based on the multi-degrees of freedom theory for gear deviation, the gear profile error and the helix error were evaluated by local degree regression and holistic degree regression. The coordinate measuring points on a cylindrical gear were used as an example for error calculation. The results are well consistent with the characterized curves measurement using a coordinate measuring machine, and the difference is within 0.5 μm. These results show that the proposed gear profile orthogonal distance regression is reasonable and effective, and it can be applied to the gear inspection using coordinate measuring machines.

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    LIN Hu, SHI Zhao-yao, XUE Zi, YANG Guo-liang. Evaluation of gear errors based on orthogonal distance regression gear profile[J]. Optics and Precision Engineering, 2015, 23(11): 3192

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    Paper Information

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    Received: Apr. 14, 2015

    Accepted: --

    Published Online: Jan. 25, 2016

    The Author Email: Hu LIN (linhu@nim.ac.cn)

    DOI:10.3788/ope.20152311.3192

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