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      Compensation of Rotary Encoders Using Fourier Expansion-Back Propagation Neural Network Optimized by Genetic Algorithm

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          Abstract

          The measurement accuracy of the precision instruments that contain rotation joints is influenced significantly by the rotary encoders that are installed in the rotation joints. Apart from the imperfect manufacturing and installation of the rotary encoder, the variations of ambient temperature could cause the angle measurement error of the rotary encoder. According to the characteristics of the 2 π periodicity of the angle measurement at the stationary temperature and the complexity of the effects of ambient temperature changes, the method based on the Fourier expansion-back propagation (BP) neural network optimized by genetic algorithm (FE-GABPNN) is proposed to improve the angle measurement accuracy of the rotary encoder. The proposed method, which innovatively integrates the characteristics of Fourier expansion, the BP neural network and genetic algorithm, has good fitting performance. The rotary encoder that is installed in the rotation joint of the articulated coordinate measuring machine (ACMM) is calibrated by using an autocollimator and a regular optical polygon at ambient temperature ranging from 10 to 40 °C. The contrastive analysis is carried out. The experimental results show that the angle measurement errors decrease remarkably, from 110.2″ to 2.7″ after compensation. The mean root mean square error (RMSE) of the residual errors is 0.85″.

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            How many hidden layers and nodes?

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                03 May 2020
                May 2020
                : 20
                : 9
                : 2603
                Affiliations
                School of Instrument Science and Opto-Electronics Engineering, Hefei University of Technology, Hefei 230009, China; huakun_jia@ 123456mail.hfut.edu.cn (H.-K.J.); jiangyizhou1@ 123456mail.hfut.edu.cn (Y.-Z.J.); hnzhao@ 123456mail.hfut.edu.cn (H.-N.Z.); cjmsaw1113@ 123456163.com (J.-M.C.)
                Author notes
                [* ]Correspondence: liandongyu@ 123456hfut.edu.cn ; Tel.: +86-138-5606-1480
                Author information
                https://orcid.org/0000-0002-0909-5507
                https://orcid.org/0000-0002-1305-4003
                Article
                sensors-20-02603
                10.3390/s20092603
                7273209
                32375212
                e98f54bc-b2c8-42fa-933e-041d36245770
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 23 March 2020
                : 30 April 2020
                Categories
                Article

                Biomedical engineering
                angle measurement error,bp neural network,genetic algorithm,rotary encoder,temperature compensation,instrument

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