WeChat Mini Program
Old Version Features

光源谱宽对法布里-珀罗干涉式光纤传感器工作灵敏度的影响

Acta Optica Sinica(2004)SCI 4区

Cited 3|Views2
Abstract
对干涉式光纤传感器来说,光源的谱宽直接影响着传感器的工作特性.从法布里-珀罗干涉式光纤传感器出发,推导其灵敏度的理论表达式,并用MathCAD软件进行了数学分析,讨论了光源谱宽对传感器灵敏度的影响.介绍了具有温度反馈功能的法布里-珀罗光纤干涉实验系统,给出了用该实验系统拍摄的谐振曲线照片.从该系统进行的两个重要的实验(不同干涉腔长的灵敏度对比实验和不同干涉长度的光源实验)表明,法布里-珀罗干涉式光纤传感器的灵敏度与光源谱宽的理论表达式是正确的,理论公式与实验结论能很好地吻合.最后指出了该方法可以用于分析其他类型的干涉式光纤传感器的灵敏度问题,为光源的选择提供了参考.
More
Translated text
Key words
Optic fiber,Optic interference,Sensitivity,Sensor,Spectrum width
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined