Temperature drift modeling and compensation of RLG based on PSO tuning SVM

This paper presents modification of Radial Basis Function Artificial Neural Network (RBF ANN)-based temperature compensation models for Interferometric Fiber Optical Gyroscopes (IFOGs) Based on the mathematical expression of IFOG output, three temperature relevant terms are extracted, which include: (1) temperature of fiber loops; (2) temperature variation of fiber loops; (3) temperature product term of fiber loops Then, the input-modified RBF ANN-based temperature compensation scheme is established, in which temperature relevant terms are transferred to train the RBF ANN Experimental temperature tests are conducted and sufficient data are collected and post-processed to form the novel RBF ANN Finally, we apply the modified RBF ANN based on temperature compensation model in two IFOGs with temperature compensation capabilities The experimental results show the proposed temperature compensation model could efficiently reduce the influence of environment temperature on the output of IFOG, and exhibit a better temperature compensation performance than conventional scheme without proposed improvements

https://www.mdpi.com/1424-8220/15/5/11189/pdf

Modification of an RBF ANN-Based Temperature Compensation Model of Interferometric Fiber Optical Gyroscopes.

To overcome the effect of temperature on laser gyro zero bias and to stabilize the laser gyro output, this study proposes a modified radial basis function neural network (RBFNN) based on a Kohonen network and an orthogonal least squares (OLS) algorithm. The modified method, which combines the pattern classification capability of the Kohonen network and the optimal choice capacity of OLS, avoids the random selection of RBFNN centers and improves the compensation accuracy of the RBFNN. It can quickly and accurately identify the effect of temperature on laser gyro zero bias. A number of comparable identification and compensation tests on a variety of temperature-changing situations are completed using the multiple linear regression (MLR), RBFNN and modified RBFNN methods. The test results based on several sets of gyro output in constant and changing temperature conditions demonstrate that the proposed method is able to overcome the effect of randomly selected RBFNN centers. The running time of the method is about 60 s shorter than that of traditional RBFNN under the same test conditions, which suggests that the calculations are reduced. Meanwhile, the compensated gyro output accuracy using the modified method is about 7.0 × 10−4 °/h; comparatively, the traditional RBFNN is about 9.0 × 10−4 °/h and the MLR is about 1.4 × 10−3 °/h.

Laser Gyro Temperature Compensation Using Modified RBFNN

Traditional compensation methods using temperature-related parameters have little effect when the ring laser gyroscope (RLG) bias changes rapidly. To solve this problem, a novel RLG bias temperature compensation method using readout signals is proposed in this paper. Combined with the least squares support vector machine (LS-SVM) algorithm, the novel method can improve the precision of the RLG bias. Experiments show that by utilizing the readout signals in the LS-SVM model, the RLG bias stability can be significantly raised compared to the original data. The novel method proposed in this paper is shown to be feasible, even when the RLG bias changes rapidly.

Temperature compensation method using readout signals of ring laser gyroscope

To further improve ring laser gyroscope (RLG) bias stability, a multiple-point temperature gradient algorithm is proposed for RLG bias compensation in this paper. Based on the multiple-point temperature measurement system, a complete thermo-image of the RLG block is developed. Combined with the multiple-point temperature gradients between different points of the RLG block, the particle swarm optimization algorithm is used to tune the support vector machine (SVM) parameters, and an optimized design for selecting the thermometer locations is also discussed. The experimental results validate the superiority of the introduced method and enhance the precision and generalizability in the RLG bias compensation model.

/pdf/multiple-point-temperature-gradient-algorithm-for-ring-laser-i6ix0j61tl.pdf

Multiple-Point Temperature Gradient Algorithm for Ring Laser Gyroscope Bias Compensation.

This thesis studies the bias drift compensation of ring laser gyro (RLG) against external environment, especially thermal effects. Bias drift is linearly proportional to temperature, and temperature gradient. So thermal effects can be removed from gyro in terms of temperature, temperature gradient. This study also shows analytically the temperature change rate and temperature gradient has same effect on the gyro.

Son Seong Hyun

Papers

The compensation method for thermal bias of ring laser gyro

Apparatus of manufacturing shell for resonators by using a laser