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铁路货运车辆运行状态安全评估问题,对预防货物列车行车事故、减少轨道车辆零部件损伤具有重要作用,对于铁路安全运营管理有着明确的指导意义。本文针对目前铁路货运车辆运行状态研究存在的不完整性问题,采用自然环境与设备运营相结合的综合车辆状态评估方法,建立面向安全的铁路货运车辆运行状态评估指标体系,并提出了一种由三部分组成的、串形结构的改进BP神经网络,更好地解决了这类数据量庞大的复杂系统评估问题。本文以沪宁线为背景进行了评估实例研究,取得了准确性较高的评估结果。
The safety assessment of the operation status of railway freight vehicles plays an important role in preventing traffic accidents of freight trains and reducing the damage of railway vehicle parts. It has a clear guiding significance for the railway safety operation and management. In this paper, according to the incompleteness of the current research status of railway freight vehicles, an integrated vehicle condition assessment method based on the combination of natural environment and equipment operation is established to establish a safety assessment indicator system for railway freight vehicles. The three-part, string-structured improved BP neural network solves the problem of complex system evaluation with large amount of data. In this paper, the evaluation of the case of the Shanghai-Nanjing line as the background of the study, and achieved a higher accuracy of the assessment results.