I-Corps: Artificial intelligence-based software package for end-to-end structural health monitoring of infrastructure systems

I-Corps：基于人工智能的软件包，用于基础设施系统的端到端结构健康监测

• 批准号: 2306180
• 负责人: Togay Ozbakkaloglu
• 金额: $ 5万
• 依托单位: Texas State University - San Marcos
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-15 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2306180&HistoricalAwards=false
• 关键词: Corps; Artificial; intelligence; based; software

The broader impact/commercial potential of this I-Corps project is the development of technology that uses the internet-of-things and/or fiber optic-based monitoring systems to solve problems faced by structural health monitoring companies related to data processing, interpretation, and storage. During its service life, civil infrastructure should satisfy the requirement of safety and sustainability for the designated operation. However, due to natural disasters and extreme events (such as strong winds and earthquakes), structures degrade in performance over time, or they get damaged severely and even collapse. For example, America's Infrastructure received an overall grade of C- according to the American Society of Civil Engineers Report Card 2021, indicating that the nation's infrastructure is in mediocre condition, has deficiencies, and needs attention. Structural health monitoring systems have gained rapid popularity in providing real-time information for the safety assessment of structures. However, structural health monitoring companies worldwide are facing challenges in data processing, interpretation, and storage, which limits their ability to obtain sufficiently comprehensive information about the health of infrastructure asset that is being monitored.This I-Corps project is based on the development of smart and effective data processing, interpretation, and storage in the structural health monitoring systems using conventional artificial intelligence and computational intelligence. Conventional artificial intelligence in this technology will describe the problem and build logical reasoning using explicit rules. Computational intelligence, which comprises an interconnected network of simple units, will be used to acquire information about the output from specific input data. The novelty of this innovation includes the development of a hybrid system by incorporating new techniques from both conventional artificial intelligence and computational intelligence to automatically accomplish the process of data acquisition and data analysis. A provision of cloud services in the core technology is used to store data before and after analysis and evaluation for further processing. Finally, this technology will interpret analyzed data to detect and locate damages and make decisions on the deterioration level of an infrastructure asset. This will allow the system to determine the required actions before danger occurs. This technology will provide an effective way for data processing, interpretation, and storage in monitoring systems in real-time by dividing the processes into three main components, namely checking for plausibility, short-term data analysis, and long-term data analysis.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.

该I-Corps项目的更广泛的影响/商业潜力是使用技术和/或基于光纤的监测系统的技术开发来解决与数据处理，解释和存储相关的结构健康监测公司所面临的问题。在服务寿命期间，民事基础设施应满足指定操作的安全性和可持续性的要求。但是，由于自然灾害和极端事件（例如强风和地震），随着时间的流逝，结构会降低性能，或者它们受到严重损害，甚至崩溃。例如，根据美国土木工程师协会报告卡2021年，美国的基础设施获得了C的总成绩，这表明该国的基础设施处于中等状态，患有不足，需要注意。结构性健康监测系统在提供实时信息以进行结构的安全评估方面已获得了迅速的知名度。然而，全球结构性健康监测公司在数据处理，解释和存储方面面临着挑战，这限制了他们获得有关正在监视的基础设施资产健康的足够全面信息的能力。此I-Corps项目基于智能和有效的数据处理，解释，以及在结构健康监测系统中使用常规人为的智能和计算的智能数据处理，解释，解释，以及在智能的数据处理，解释和存储中。该技术中的常规人工智能将描述问题并使用明确的规则构建逻辑推理。 计算智能包括一个互连的简单单元网络，将用于从特定输入数据中获取有关输出的信息。这项创新的新颖性包括通过结合传统人工智能和计算智能的新技术来开发混合系统，以自动完成数据获取和数据分析的过程。核心技术中云服务的规定用于在分析和评估之前和之后存储数据以进行进一步处理。最后，这项技术将解释经过分析的数据，以检测和定位损害赔偿，并在基础设施资产的恶化水平上做出决策。 这将允许系统在危险发生之前确定所需的动作。该技术将通过将过程分为三个主要组成部分来实时监控系统中的数据处理，解释和存储，即检查合理性，短期数据分析和长期数据分析。这项奖项反映了NSF的法规任务，并认为通过基金会的知识优点和广泛的critia criter criter scriter criter criter criter criter criter criteria criter criteria criter criteria criter criteria criter criteria criter criteria criteria criter criteria均值得通过评估。