CPS: Medium: Collaborative Research: Frequency Domain Conversion of Computer Aided Design Files to Enable Encryption, Authentication and Feature Search Function

增材制造（AM）或3D打印市场已从2009年的11亿美元呈指数级增长至2018年的73亿美元，专家估计这一数字将在未来四年内翻一番。尽管计算机辅助设计（CAD）文件在AM中发挥着战略性作用，但设计师开发，存储和使用CAD模型，就像他们在任何其他制造方法中一样。本研究将研究一种新的方法，赋予新的功能，在CAD模型转换到频域使用无损算法。频域表示允许在文件中搜索感兴趣的特定设计特征，这在当前CAD文件格式中是不可行的。向频域的变换为开发新的压缩和加密方法开辟了可能性。将进行分析，以确定导致CAD文件到频域的无损转换的基本原则，并开发文件的压缩和加密方法。小波变换和动态时间规整将是用于实现搜索功能的方法之一。动态窗口选择和缩放方法将用于在缩放和不缩放对象大小的情况下执行特征搜索。这些算法基于精确匹配过程，并且不依赖于调整或学习算法。 该项目将帮助使用AM方法的行业，例如航空航天，汽车，医疗和军事设备行业。这些独特能力的开发将为设计、搜索和安全提供新的能力。该项目将涉及博士后研究员和研究生的研究。传播计划将包括在期刊、会议报告和新闻稿中公布研究结果，通过新闻媒体提高公众意识。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The additive manufacturing (AM) or 3D printing market has developed exponentially from $1.1B in 2009 to $7.3B in 2018 and experts estimate this to grow double in the next four years. Despite the strategic role that computer-aided design (CAD) files play in AM, designers develop, store, and use the CAD models as they do in any other manufacturing method. This study will research a novel method of imparting new functionalities in CAD models by converting them to the frequency domain using lossless algorithms. The frequency domain representation allows searching the files for specific design features of interest, which is not feasible in the current CAD file formats. Transformation to the frequency domain opens up possibilities for developing new compression and encryption methods. Analysis will be conducted to determine the fundamental principles that lead to lossless conversion of CAD files to the frequency domain and develop compression and encryption methods for the files. Wavelet transform and dynamic time warping will be among the methods used for implementing search functionalities. Dynamic window selection and scaling methods will be used to perform feature search with and without scaling of the object size. These algorithms are based on an exact match procedure and do not rely on tuning or learning the algorithm. The project will help industries that are using AM methods, for example, the aerospace, automotive, medical and military equipment industries. Development of these unique capabilities will by provide new capabilities for design, search, and security. The project will involve post-doctoral fellows and graduate students in the research. The dissemination plan will include publishing the results in journals, conference presentations and press releases for public awareness using the news media.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.