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在石英柔性加速器中补偿温度诱导的错误,使用基于多项式的非均突变遗传算法框架

Jinyue Zhao¹, Kunpeng He¹, Kang Le¹

¹College of Artificial Intelligence, Nankai University, Tianjin 300350, China.

Sensors (Basel, Switzerland)

|February 13, 2025

概括

这项研究引入了一种新的温度误差补偿方法,用于石柔性加速度计 (QFA) 在带式惯性导航系统 (SINS) 中. 该方法显著减少了由温度波动引起的偏差错误,提高了导航准确度.

科学领域:

惯性导航系统惯性导航系统
传感器技术传感器技术
计量学和测量计量学和测量

背景情况:

石英柔性加速度计 (QFA) 对于导航级的紧式惯性导航系统 (SINS) 是至关重要的.
温度变化严重影响QFA偏差和尺度因子,降低SINS导航准确度.
现有的补偿方法在处理动态温度诱导的错误时可能缺乏效率.

研究的目的:

开发和验证QFA的先进温度误差补偿方法.
为了提高SINS在不同温度条件下的导航精度.
为了利用非均突变策略的遗传算法 (NUMGA) 精确的模型参数识别.

主要方法:

分析QFA输出中的温度偏差机制.
为温度误差建立一个多项式曲线模型 (PCF).
使用非统一突变策略遗传算法 (NUMGA) 优化PCF参数,数据范围为-20至40°C.

主要成果:

NUMGA-PCF模型有效地确定了最佳参数,证明了稳定的适应曲线.
与传统GA方法相比,在SINS中的QFA三个轴上的补偿误差显著减少:612.24μg,60.82μg和875.82μg.
维持QFA偏差的平均值和标准偏差在-20~40°C范围内低于0.1μg.

结论:

拟议的NUMGA-PCF方法为QFA中的温度误差补偿提供了强大而准确的解决方案.
这种方法提高了SINS在热应力下的整体导航精度和稳定性.
该方法通过在广泛的温度范围内保持低偏差误差,确保可靠的性能.

关键词:

错误补偿错误补偿错误补偿错误补偿参数识别参数识别石英柔性加速度计 (QFA) 是一种柔性加速度计.带绳式惯性导航系统 (SINS) 是一个系统.温度错误建模的温度错误建模

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