Artificial Intelligence Aproaches as Tools for Auditing and Improving Data Analysis of Advanced Ultrasound Techniques in Non-Destructive Testing

Neil Harrap, R. Rhéaume, A. Gosselin
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引用次数: 1

Abstract

Advanced Non Destructive Testing (NDT) techniques rely on consistent acquisition of data and its reliable analysis. As technology advances, new challenges emerge. For instance, the amount of data produced is exceeding the qualified personnel available for data analysis; moreover, the files produced can be easily handle unethically. Our project proposes the implementation of Artificial Intelligence (AI) techniques to develop algorithms to better harness the data available, in order to enhance the quality of data analysis and better monitor ethical practices. Method: For any NDT technique, the consistency of the results and the reliability of the findings depends heavily on the personnel performing the inspections and evaluating the results. As more advanced NDT techniques are available in the areas of ultrasound, digital data becomes available opening the door for intelligent tools for analysing and handling ultrasound data. This project proposes an innovative analysis software based on Computational Intelligence (CI) techniques. The implementation of this software reduces the time needed for a single analysis and the consistency of results, more importantly; it can be use as an audit tool to ensure data files have not been mishandle. For the first stage of the proposed CI cloud-based software, the data collected by the inspector is send via internet connection to web-based servers. During the second stage, the data will be verify for quality; if any data is missing or poor-quality is detected, the software will inform the inspector that data must be resubmitted. Once the verification of data is completed, the data analysis is then perform by CI-based algorithms, which can recognise and classify features within the data such as geometry indications, anomalies and defects. Following the CI-based analysis, the software generates a complete report and the results are be available to the user via a 3D visualization interface. This report includes details of sizing, characterisation, location of defects, geometry indications and other relevant information related to the analysed data. The information contained in the interface and generated by the software will be available to the final user for validation and approval. The CI-based analysis tools have already been use to monitor several data files from NDT inspections using Phased Array Ultrasound (PAUT) and the results have successfully verify the authenticity of the ultrasound raw data, which is a critical verification step and evidence of any mal practices or mistakes of data handling. There is a lack of reliable tools available to NDT experts that can facilitate the task of analysing data; this innovative software takes advantage of the CI techniques and expert knowledge to address this issue. Furthermore, our approach offers a high degree of consistency for identifying defects; improves the quality of the analysis and reduces the time invested in such critical NDT duty. Auditing raw data from ultrasound inspection is a challenging task; by taking advantage of CI-based analysis tools this task can be easily implement it as reliable auditing practice.
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人工智能方法作为审计和改进无损检测中先进超声技术数据分析的工具
先进的无损检测(NDT)技术依赖于一致的数据采集和可靠的分析。随着技术的进步,新的挑战也随之而来。例如,产生的数据量超过了可用于数据分析的合格人员;此外,生成的文件很容易被不道德地处理。我们的项目建议实施人工智能(AI)技术来开发算法,以更好地利用现有数据,以提高数据分析的质量并更好地监控道德实践。方法:对于任何无损检测技术,结果的一致性和发现的可靠性在很大程度上取决于执行检查和评估结果的人员。随着超声领域更先进的无损检测技术的出现,数字数据的出现为分析和处理超声数据的智能工具打开了大门。本课题提出一种基于计算智能(CI)技术的创新分析软件。该软件的实现减少了单次分析所需的时间和结果的一致性,更重要的是;它可以用作审计工具,以确保数据文件没有被错误处理。对于提议的基于云的CI软件的第一阶段,检查员收集的数据通过互联网连接发送到基于web的服务器。在第二阶段,将验证数据的质量;如果检测到任何数据缺失或质量差,软件将通知检查员必须重新提交数据。一旦数据验证完成,数据分析将由基于ci的算法执行,该算法可以识别和分类数据中的特征,如几何指示、异常和缺陷。在基于ci的分析之后,软件生成完整的报告,并通过3D可视化界面向用户提供结果。该报告包括尺寸、特征、缺陷位置、几何指示和与分析数据相关的其他相关信息的详细信息。界面中包含的信息和软件生成的信息将提供给最终用户进行验证和批准。基于ci的分析工具已经被用于监测相控阵超声(PAUT)无损检测的几个数据文件,结果成功验证了超声原始数据的真实性,这是一个关键的验证步骤,也是数据处理不当或错误的证据。无损检测专家缺乏可用于促进数据分析任务的可靠工具;这个创新的软件利用CI技术和专业知识来解决这个问题。此外,我们的方法为识别缺陷提供了高度的一致性;提高了分析的质量,减少了在这种关键的无损检测任务上投入的时间。审核超声检查的原始数据是一项具有挑战性的任务;通过利用基于ci的分析工具,可以轻松地将此任务实现为可靠的审计实践。
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