摘要
针对我国车辆定期检修时间较长、工作量大、车辆运用率低等问题,通过计算货车运行里程,分析货车的健康状况,构建了数学模型,搭建出货车运行管理系统整体运算框架,利用车号识别系统,结合现有的设备条件建立了计算模型,实现了货车运行里程的自动统计。融入分配模型对货车运行里程的计算进行优化,采用基于深度学习的多线程并行计算方法,提高了数据管理能力,试验表明,本研究方法效率更高,实时性更好。
Aiming at the shortcomings of long regular maintenance time, heavy workload and low utilization rate of vehicles in China, this paperanalyzes the health status of trucks, constructs a mathematical model, builds the overall operation framework of truck operation management system, by calculating the mileage of trucks and using the vehicle number. The recognition system establishes a calculation model based on the existing equipment conditions, and realizes the automatic statistics of the mileage of trucks. It alsoincorporates the distribution model to optimize the calculation of truck mileage, and adopts the multi-threaded parallel calculation method based on deep learning to improve the data management ability. Tests show that the research method is more efficient and has better real-time performance.
作者
边志宏
牛丽娟
BIAN Zhihong;NIU Lijuan(National Energy Group Shenhua Railway Equipment Co.,Ltd.,Beijing 100120,China;Beijing Jingtianwei Technology Development Co.,Ltd.,Beijing 100085,China)
出处
《微型电脑应用》
2022年第12期153-156,共4页
Microcomputer Applications
关键词
铁路货车
标签识别
运行里程计算
分配模型
多线程并行计算
railway freight car
label recognition
mileage calculation
allocation model
multi thread parallel computing