• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >Polymer Optical Fiber Sensor and the Prediction of Sensor Response Utilizing Artificial Neural Networks.
【24h】

Polymer Optical Fiber Sensor and the Prediction of Sensor Response Utilizing Artificial Neural Networks.

机译：聚合物光纤传感器及利用人工神经网络的传感器响应预测。

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The global market researches showed that there is a growing trend in the field of polymer optical fiber (POF) and POF sensors. Telecommunications, medicine, defense, aerospace, and automotive are the application areas of fiber optic sensors, where the automotive industry is the most promising application area for innovations in the field of POF sensors. The POF sensors in automobiles are particularly for detection of seat occupancy, and intelligent pedestrian protection systems.;This dissertation investigates graded index perfluorinated polymer optical fiber as an intensity modulated intrinsic sensor for application in automotive seat occupancy sensing. Since a fiber optic sensor has a high bandwidth, is small in size, is lightweight, and is immune to electromagnetic interference (EMI) it offers higher performance than that of its electrical based counterparts such as strain gauge, elastomeric bladder, and resistive sensor systems. This makes the fiber optic sensor a potential suitable material for seat occupancy sensing.;A textile-based fiber optic sensor was designed to be located in the area beneath the typical seated human's thighs. The pressure interval under which the proposed POF sensor design could perform well was found to be between 0.18 and 0.21 N/cm2, where perfluorinated (PF) graded index (GI) POF (62.5/750 mum) was used as the POF material. In addition, the effect of the automotive seat covering including face material (fabric) and foam backing to the sensor's performance was analyzed. The face fabric structure and the thickness of foam backing were not found to be significant factors to change the sensor results.;A research study, survey, was conducted of which purpose was to better understand market demands in terms of sensor performance characteristics for automotive seat weight sensors, as a part of the Quality Function Deployment (QFD) House of Quality analysis. The companies joined the survey agreed on the first 5 most important sensor characteristics: reproducibility, accuracy, selectivity, aging, and resolution.;Artificial neural network (ANN), a mathematical model formed by mimicking the human nervous system, was used to predict the sensor response. Qwiknet (version 2.23) software was used to develop ANNs and according to the results of Qwiknet the prediction performances for training and testing data sets were 75%, and 83.33% respectively.;In this dissertation, Chapter 1 describes the worldwide plastic optical fiber (POF) and fiber optic sensor markets, and the existing textile structures used in fiber optic sensing design particularly for the applications of biomedical and structural health monitoring (SHM). Chapter 2 provides a literature review in detail on polymer optical fibers, fiber optic sensors, and occupancy sensing in the passenger seats of automobiles. Chapter 3 includes the research objectives. Chapter 4 presents the response of POF to tensile loading, bending, and cyclic tensile loading with discussion parts. Chapter 5 includes an e-mail based survey to prioritize customer needs in a Quality Function Deployment (QFD) format utilizing Analytic Hierarchy Process (AHP) and survey results. Chapter 6 describes the POF sensor design and the behavior of it under pressure. Chapter 7 provides a data analysis based on the experimental results of Chapter 6. Chapter 8 presents the summary of this study and recommendations for future work.
机译：全球市场研究表明，聚合物光纤（POF）和POF传感器领域中存在增长的趋势。电信，医学，国防，航空航天和汽车领域是光纤传感器的应用领域，其中汽车行业是POF传感器领域创新的最有希望的应用领域。汽车中的POF传感器尤其适用于座椅占用检测和智能行人保护系统。;本论文研究了渐变指数全氟化聚合物光纤作为强度调制的本征传感器，用于汽车座椅占用传感。由于光纤传感器具有高带宽，体积小，重量轻且不受电磁干扰（EMI）的影响，因此与基于电气的同类产品（如应变仪，弹性囊和电阻式传感器系统）相比，其性能更高。 。这使光纤传感器成为用于座位占用感测的潜在合适材料。基于纺织品的光纤传感器被设计为位于典型的就座大腿下方的区域。发现建议的POF传感器设计可以很好地发挥作用的压力间隔在0.18和0.21 N / cm2之间，其中全氟化（PF）渐变指数（GI）POF（62.5 / 750 mum）被用作POF材料。此外，还分析了包括面材料（织物）和泡沫背衬在内的汽车座椅套对传感器性能的影响。面罩的结构和泡沫背衬的厚度未发现是改变传感器结果的重要因素。；进行了一项研究，调查，目的是从汽车座椅的传感器性能特征方面更好地了解市场需求。重量传感器，作为质量功能部署（QFD）质量分析之家的一部分。参加调查的公司同意了前5个最重要的传感器特性：可重复性，准确性，选择性，老化和分辨率。人工神经网络（ANN）是模仿人类神经系统形成的数学模型，用于预测传感器的传感器响应。使用Qwiknet（2.23版）软件开发人工神经网络，根据Qwiknet的结果，训练和测试数据集的预测性能分别为75％和83.33％.;在本文中，第1章介绍了全球塑料光纤（ POF）和光纤传感器市场，以及用于光纤传感设计的现有纺织结构，特别是用于生物医学和结构健康监测（SHM）的应用。第2章详细介绍了聚合物纤维，光纤传感器以及汽车乘客座椅中的占用感应的文献综述。第三章包括研究目标。第4章通过讨论部分介绍了POF对拉伸载荷，弯曲和循环拉伸载荷的响应。第5章包括基于电子邮件的调查，以利用分析层次结构过程（AHP）和调查结果以质量功能部署（QFD）格式对客户需求进行优先级排序。第6章介绍了POF传感器的设计及其在压力下的行为。第7章根据第6章的实验结果提供了数据分析。第8章介绍了本研究的摘要以及对未来工作的建议。

著录项

  • 作者

    Haroglu, Derya.;

  • 作者单位

    North Carolina State University.;

  • 授予单位 North Carolina State University.;
  • 学科 Textile Technology.;Engineering Materials Science.;Business Administration Management.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 276 p.
  • 总页数 276
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号