游标类量具检定装置的驱动系统误差补偿

doi:10.3969/j.issn.1000-1158.2018.03.08

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Abstract In the verification process of vernier measuring tools, when the dynamic table of the drive system in the verification device is at a low speed, the errors of the friction and backlash nonlinearity are exist between the dynamic work station and the ball screw, so the vernier measuring tools cannot be accurately moved to the test point required by the verification procedure. In order to solve the problem of the errors, the LuGre friction model and adaptive periodic recursive wavelet neural network are used to compensate the friction and backlash nonlinearity.Based on the Liroff stability analysis, the boundedness and convergence of the closed-loop system are guaranteed.The simulation results show that the performance of position tracking is improved, and the control compensation scheme is demonstrated in the driving system of the verification device, the accuracy of positive is improved by 47.6% in positive movement and 49.7% in negative movement.

Key words： metrology vernier gauge driving system nonlinear compensation recurrent wavelet neural networks

Received: 18 August 2017 Published: 12 April 2018

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TB921

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	Articles by authors
	CHEN Wang-da
	XU Zhi-ling
	LI Zhi-fei

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CHEN Wang-da,XU Zhi-ling,LI Zhi-fei. Error Compensation of Drive System of Vernier Measuring Instrument[J]. Acta Metrologica Sinica, 2018, 39(3): 326-331.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2018.03.08 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2018/V39/I3/326

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