基于信息标准的高精度位移传感器的新型信息驱动光滑线条线性化方法
Wen-Hao Zhang1, Lin Dai1, Wang Chen1
1State Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310058, China.
Sensors (Basel, Switzerland)
|November 25, 2023
概括
一种新的光滑螺纹线性化方法准确地纠正传感器非线性,显著提高位移测量精度. 这种耐噪方法提高了高精度位移传感器的精度,优于传统模型.
科学领域:
- 计量学和测量科学 计量学和测量科学
- 传感器技术 传感器技术
- 数据分析和建模
背景情况:
- 从传感器信号中准确的物理位移检索需要耐噪声的线性化模型.
- 对于高精度测量,必须揭示真正的传感器非线性.
- 现有的多项式和分线方法在低噪声到距离比率的场景中存在局限性.
研究的目的:
- 为高精度位移传感器提出一种新的信息驱动的光滑线线性化方法.
- 整合信息标准,以提高线性化性能.
- 评估拟议的方法与传统技术相比.
主要方法:
- 开发了一种信息驱动的平滑线条线性化技术.
- 将一个新的和三个标准的信息标准集成到spline模型中.
- 使用理论分析和蒙特卡洛模拟进行评估.
- 在色彩对焦和激光三角化位移传感器上进行了验证实验.
主要成果:
- 提出的方法显著优于传统的多项式和线条线性化方法.
- 整合修改后的Akaike信息标准显示出卓越的性能.
- 与标准多项式模型相比,剩余非线性得到了50%以上的改进.
- 实现的剩余非线性低至±0.0311%的FS. 和 ±0.0047% 的FS. 对于经过测试的传感器.
结论:
- 新型信息驱动的光滑线线性化方法为高精度位移传感器提供了卓越的精度.
- 该方法有效地减轻噪声,并揭示真正的传感器非线性.
- 这种方法在移位传感技术方面取得了重大进展.
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