Automation of Tenanted Arches NDT Inspections using Robotics and Machine Learning
Automation of Tenanted Arches NDT Inspections using Robotics and Machine Learning
批准号:
10089475
负责人:
金额:
$41.21万
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
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英文摘要
This innovative project that aims to automate the inspection of cladded tenanted arches without the need to remove the cladding, and to also detect sub-surface defects in the arches, which is not currently possible with current methods. The project will focus on the use of robotics devices coupled with Non-Destructive Testing (NDT) techniques such as Ground Penetrating Radar (GPR) and X-ray Backscatter (XBS) to build an accurate and 3D picture of the overall health of the tenanted arches.This proposal is a continuation of the successful activities between the MTC and Network Rail, the Tenanted Arches Project stream, in which GPR and XBS technologies were utilised to manually scan cladded tenanted arches within Greater London, quickly and without the need to remove or damage any cladding. In the latest stages of the project, it was possible to manually collect the required data and then quickly produce human readable information about the size and location of all relevant defects behind the cladding material. All the inspection thus far has been completed manually by operators, so this proposal will focus on fully automating the process such that it is faster and safer.The proposed project involves four main activities: defining an automation platform for robotics devices to inspect tenanted arches without cladding removal, enhancing data processing techniques to improve image quality in the NDT scans, deploying machine learning algorithms for automated defect detection and visualisation in 3D space, and conducting a proof-of-concept demonstration to showcase the integration of systems and sensors. By automating inspections, enhancing data analysis, and leveraging advanced technologies, the project aims to streamline tenanted arch inspections, increase the quality and quantity of collected information, and improve predictive maintenance scheduling. Ultimately, the project will provide a safer, faster, and more reliable inspection solution for cladded tenanted arches in railway infrastructure.
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