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Field Data based Predictive Maintenance and Enhanced Track Design Procedure

Field Data based Predictive Maintenance and Enhanced Track Design Procedure
基于现场数据的预测性维护和增强的轨道设计程序
批准号:
LP200200915
负责人:
Prof Buddhima Indraratna
金额:
$50.18万
依托单位国家:
澳大利亚
项目类别:
Linkage Projects
财政年份:
2021
资助国家:
澳大利亚
项目状态:
已结题
起止时间:
2021-09-04 至 2024-09-03

项目摘要

项目成果

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中文摘要
翻译
提供经过改进的铁路设计和维护解决方案,并对轨道性能进行准确和及时的评估,对于减少服务中断、过高的维护成本和随着时间的推移而退化至关重要。该项目旨在开发一种基于广泛的路旁测量的预测性维护模型,以监测和预测轨道不稳定的性质。此外,还将建立数学模型,用过去和实时的实地监测记录来证实大规模实验室观察结果。该项目将提供切实的战略和工具,以增加轨道寿命,并协助决策者规划和确定纠正性维护的优先顺序,以确保提高安全性和乘客舒适性。
英文摘要
Providing improved railroad design and maintenance solutions with accurate and timely assessment of track performance is vital to reduce the disruption of services, excessive maintenance costs and degradation over time. This project aims to develop a predictive maintenance model based on extensive wayside measurements to monitor and predict the nature of track instability. This will also be supplemented by mathematical modelling to corroborate large-scale laboratory observations with past and real-time field monitoring records. This project will deliver tangible strategies and tools to increase track longevity and assist decision-makers in planning and prioritising corrective maintenance to ensure improved safety and passenger comfort.
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会议论文
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国内基金
海外基金
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