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Issue title: Artificial Intelligent Techniques and its Applications
Guest editors: Mahalingam Sundhararajan, Xiao-Zhi Gao and Hamed Vahdat Nejad
Article type: Research Article
Authors: Shi, Zhen | Yang, Zhiqiang; * | He, Kaiying
Affiliations: School of Geology Engineering and Geomatics, Chang’an University, Xi’an, Shaanxi, China
Correspondence: [*] Corresponding author. Zhiqiang Yang, School of Geology Engineering and Geomatics, Chang’an University, Xi’an, Shaanxi, China. E-mail: e8048889jiaomen@163.com.
Abstract: A north-seeking data quality optimization method for a magnetically suspended gyroscope is proposed based on two-position characteristics combined with the north-seeking characteristic principle of the magnetically suspended gyroscope total station theodolite. First, a simple linear regression model is established based on the linear relationship satisfied by the rotor current of two precise seeking positions and the north-seeking azimuth. Then, the confidence interval of the corresponding rotor current is calculated from the a priori value of the north-seeking azimuth, and the rotor current data outside the confidence interval are removed. Lastly, the gyroscope azimuth is recalculated. Engineering test data were used to test the effectiveness of the method, and the results showed that the method is effective at testing the north-seeking data quality of the gyroscope and correcting directional results.
Keywords: Magnetically suspended gyroscope, data removal, quality optimization
DOI: 10.3233/JIFS-169372
Journal: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 2, pp. 787-796, 2018
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