K mean value cluster-based optical fiber inertial measurement unit temperature model coefficient determination method

Abstract

The invention discloses a K mean value cluster-based optical fiber inertial measurement unit temperature model coefficient determination method. According to optical fiber inertial measurement unit temperature model coefficient first-order subsection cases, if the number of segments is determined, 1, according to a straight line determined through adjacent temperature points, a slope is calculated, 2, through a K mean value clustering algorithm, the slope is classified and a category code is determined, 3, according to the category code and the number of the segments, all segment point compositions are acquired, and 4, through a fitting residual error, the optimal segment point is determined, and if the number of segments is not determined, according to a sequence of 1 to the largest probable number of the segments, the optimal segment point under the condition of each one of the numbers of the segments is calculated through the above steps 1-4 until the residual error satisfies the requirements. Finally, according to the optimal segment points, the optical fiber inertial measurement unit temperature model coefficient is fitted. The method utilizes the K mean value clustering algorithm to automatically search the optimal segment point, overcomes random errors and repeated processes of manual subsection and effectively improves product temperature model coefficient calculating efficiency and reliability.

Description

technical field [0001] The invention relates to a method for determining the temperature model coefficient of an optical fiber inertial group based on K-means clustering, and belongs to the field of optical fiber inertial group calibration testing. Background technique [0002] Fiber optic gyroscope inertial combination has the advantages of high reliability, long life, fast startup, low power consumption, relatively simple production process, etc., so it has been widely promoted and applied in military equipment and civilian fields. In the production process of the inertial group of fiber optic gyro, the adjustment and testing link is an indispensable step before the inertial group leaves the factory. In addition to screening out unqualified products, an important task in this link is the calibration of the inertial group. The most complicated work in the calibration is the establishment of the fiber inertial temperature model and the calculation of the temperature model co...

AI Technical Summary

Problems solved by technology

When the first-order fitting method is used to calculate the optical fiber inertial group scale factor or zero model coefficient, it is necessary to segment the relationship between the optical fiber inertial group scale factor or zero position and temperature, and use the temperature segmentation point and its The temperature model coefficients are obtained by first-order fitting of the corresponding scale factor or zero position. In the prior art, the segmentation points usually need to be manually judged by technicians through experience, and then the fitting calculation is carried out. For those with rich experience , it takes a short time to manually judge the segmentation points by visual inspection, and a more suitable result may be obtained once or twice, but for those who are not familiar with the performance of the product and the operation, it often takes several comparisons to meet the requirements Calculate the fitting value closest to the true value at the temperature segment point

In addition, no matter whether you are familiar with the segmentation operation or not, manual visual segmentation points are always full of uncertainty and random errors. There will be certain differences in different judgments by different personnel and the same personnel, and it is impossible to fundamentally guarantee the accuracy of the segmentation operation. Consistency and consistency, thus restricting the calculation efficiency and reliability of the product temperature model coefficients, there are certain hidden dangers to product quality

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