多源数据融合的列车-轨道状态检测技术

Vehicle track state detection technology based on multi-source data fusion

轨道状态的快速检测技术是保障轨道交通运维安全的重要基础。传统的检测方法主要依赖高精密、高成本的测量设备,这些测量设备测量数据质量高但体量小。随着大数据技术的快速发展,通过易获取、质量低但体量大的多源数据融合技术以及 5G 通信与云服务技术,以多车厢加速度、轮轨噪声数据为基础,实现多源数据融合的列车-轨道状态检测技术。实践表明,多源数据融合的列车-轨道状态检测技术是实现轨道设备质量状态智能辨识和预测的有效途径。

Rapid detection technology of rail status is an important foundation to ensure the safety of rail transit operation and maintenance.Traditional detection methods mainly rely on high-precision and high-cost measuring equipment,which has high quality but small volume of measurement data.With the rapid development of big data technology,multi-source data fusion technology with easy access,low quality but large volume and 5G communication and Cloud service technology are used to realize vehicle and track state detection technology based on multi-vehicle acceleration and wheel-rail interface noise data.The practice shows that the train-track state detection technology based on multi-source data fusion is an effective way to realize intelligent identification and prediction of track equipment quality state.