Performance Evaluation of Fiber Optic Gyro Based on Nonlinear Random Effect Wiener Process

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Abstract Fiber optic gyro belongs to highly reliable and long-life components, which cannot be realized by traditional reliability assessment methods due to the difficulty of obtaining failure data; the Wiener process model can better model the degradation process of the device, thus realizing the reliability assessment based on the performance degradation. However, the performance degradation of fiber optic gyro exhibits nonlinear characteristics, and there is significant variability in degradation patterns among individual units within the same batch. Traditional Wiener process modeling fails to account for these two critical features. In this paper, a reliability assessment method based on the nonlinear random effect Wiener process is proposed. The nonlinear relationships are first transformed into linear forms through time-scale transformation, while the drift coefficients of the Wiener process are randomized to construct a more comprehensive stochastic degradation model. Subsequently, the Gibbs sampling method is introduced to achieve precise parameter estimation and model resolution. The proposed methodology is then applied to zero-bias performance degradation data from fiber optic gyros for reliability evaluation, generating corresponding reliability curves. The experiments show that the Akaike Information Criterion (AIC) value of the model in this paper is significantly reduced by 28.7% compared with the traditional method, indicating that the model achieves a better balance between complexity and goodness-of-fit. Therefore, the developed methodology provides a more accurate representation of the nonlinear degradation characteristics in fiber optic gyro, thereby significantly enhancing the credibility of the assessment outcomes.

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