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针对影响光纤陀螺精度的温度效应误差,分析了误差成因及其影响机理,建立了以温度和温度变化率为变量的二次误差模型,提出了一种基于数据分类的模型参数拟合与建模方法。在模型参数拟合时,先将陀螺的全温试验数据按不同温度条件进行分类,再分别使用各类数据进行基于最小二乘法的参数拟合,得到相应温度环境下的模型参数。在进行补偿时,先实时计算各个相关变量,进行数据类别判定,再调用对应的模型参数进行补偿计算。通过多次试验验证了该方法有效可行且通用性好,光纤陀螺精度较补偿前提高了近一个数量级。
Aiming at the error of temperature effect that affects the accuracy of FOG, the cause of error and its influence mechanism are analyzed. The quadratic error model whose temperature and temperature change rate are taken as variables is proposed and a model parameter fitting and modeling based on data classification is proposed method. When the model parameters are fitted, the temperature of the top of the gyroscope is classified according to different temperature conditions, and each parameter is used to fit the parameters based on the least square method to obtain the model parameters under the corresponding temperature conditions. When compensating, each related variable is calculated in real time, and the data type is determined, and then the corresponding model parameters are invoked for compensation calculation. Through many experiments, the method is validated and the generality is good. The precision of the optical fiber gyroscope is increased by nearly an order of magnitude compared with that before compensation.