Quantification of Railroad Ballast Performance Using Advanced Sensor Network & Big Data
| 项目名称： | Quantification of Railroad Ballast Performance Using Advanced Sensor Network & Big Data |
| 摘要： | While railroads are aware of the fact that ballast behavior has a profound influence on track performance and that ballast fouling leads to accelerated track-bed deterioration, the methods for determining ideal maintenance (e.g., tamping, ballast cleaning, etc.) have relied heavily on past experience, manual inspection, and often anecdotal information. A technology that will allow railroads to identify an objective threshold by which they can establish a window of opportunity for ideal track maintenance is in great need. This proposed research is expected to satisfy this need by implementing an advanced ballast performance monitoring program based on innovative wireless sensors and Big Data technologies. This project is anticipated to result in a real-time data collection and integrated analysis system which will allow railroad companies to identify the instantaneous condition of their ballast and track-bed more accurately and proactively assign maintenance windows to ensure safe and efficient train operation with the least amount of train delay due to maintenance outages. |
| 状态： | Active |
| 资金： | 222,002 |
| 资助组织： | Office of the Assistant Secretary for Research and Technology |
| 管理组织： | Center for Integrated Asset Management for Multimodal Transportation Infrastructure Systems (CIAMTIS) |
| 项目负责人： | Donnell, Eric T |
| 执行机构： | Pennsylvania State University, University Park<==>University of Delaware, Newark |
| 主要研究人员： | Huang, Hai；Zarembski, Allan |
| 开始时间： | 20220201 |
| 预计完成日期： | 20230831 |
| 主题领域： | Data and Information Technology；Maintenance and Preservation；Railroads |
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