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Reducing the Threat to Public Safety: Improved metallic object characterisation, location and detection

减少对公共安全的威胁：改进金属物体的特征、定位和检测

基本信息

批准号：
EP/R002134/1
负责人：
Paul Ledger
金额：
$ 41万
依托单位：
Swansea University
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2018
资助国家：
英国
起止时间：
2018 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FR002134%2F1
关键词：
Reducing Threat Public Safety Improved

项目摘要

The United Nations (UN) have announced that "With more than 30,000 foreign terrorist fighters from some 100 countries around the world, terrorism is a global threat requiring a comprehensive and unified response." This statement followed a spate of recent terrorist attacks, including those in France and Germany (July 2016), and a growing sense of global uncertainty in the western world. Promoting improvements to the identification and location of metallic threat items is an important aspect of the unified response and is an area where engineering and science can make a significant impact. Improvements in metal detection (MD) technology also provides wider benefits to the humanitarian cause of clearing landmines in developing countries. Wider benefits exist for the technology being transferred to MD companies developing devices for the non-destructive testing (NDT) of materials for safe structures, ensuring food safety, improved scrap metal sorting, as well as in medical imaging and archaeological searches.Of course current metal detectors do find highly conductive objects and their simple design (and portability) has made them a highly cost effective modality for safety and security applications. Unfortunately, current technology is not able (or has limited capability) to distinguish between objects of different shape and materials of objects and can only detect objects within a small stand-off distance (or buried depth).This proposal is aimed at overcoming these drawbacks through an interdisciplinary approach to improving MD technology, combing engineering, mathematics and scientific computation. Our hypothesis is that the response of metallic items in low frequency electromagnetic fields can be accurately described using a tensor based approximation. To test this hypothesis, we will develop a complete laboratory demonstration of our MD approach. This includes the following novel aspects: an efficient and adaptable software that can compute tensor coefficients for in-homogeneous objects, an algorithm for identifying different targets from field measurements with embedded uncertainty quantification as well as enhancing MD measurements by building new coil arrays based on optimised coil design. The goal is that our complete software and measurement package will lead to a step change in MD.

联合国(UN)宣布，“恐怖主义是一种全球性威胁，需要全面而统一的应对措施。”在发表这一声明之前，最近发生了一系列恐怖袭击，包括法国和德国(2016年7月)发生的恐怖袭击，以及西方世界日益增长的全球不确定性。促进改进金属威胁物项的识别和定位是统一应对措施的一个重要方面，也是工程和科学可以产生重大影响的一个领域。金属探测(MD)技术的改进也为发展中国家清除地雷的人道主义事业提供了更广泛的好处。将技术转让给MD公司有更广泛的好处，因为MD公司正在开发设备，用于安全结构的材料的无损检测(NDT)，确保食品安全，改进废金属分类，以及在医学成像和考古搜索中。当然，目前的金属探测器确实能发现高导电性的物体，其简单的设计(和便携性)使它们成为安全和安保应用的一种高成本效益的方式。遗憾的是，目前的技术不能(或能力有限)区分物体的不同形状和材料，只能探测到距离较小(或埋深)较小的物体。该建议旨在通过跨学科的方法来改进MD技术，结合工程、数学和科学计算。我们的假设是，金属物体在低频电磁场中的响应可以用基于张量的近似精确地描述。为了验证这一假设，我们将开发一个完整的MD方法的实验室演示。这包括以下新颖的方面：可以计算非均匀物体张量系数的高效且适应性强的软件；通过嵌入不确定性量化从现场测量中识别不同目标的算法；以及通过基于优化的线圈设计构建新的线圈阵列来增强MD测量。我们的目标是，我们的完整软件和测量包将导致MD的阶段性变化。