摘要
传统的车站接发列车作业以人检为主,劳动强度较高,存在人身安全隐患,且存在漏判和误判,难以有效保障接发列车作业质量。运用图像识别、数据挖掘、智能分析及系统集成技术,提出列车在站运行状态监测系统方案,对车站接发列车的图像、视频、车轮踏面温度、车辆运行声音等信息进行自动采集和智能分析,提供车辆异常状态识别和报警功能,实现接发列车作业从"人检"向"机检"、"室外"向"室内"、"静态"向"动态"的转变。该系统方案对提升车站接发列车作业效率和作业质量,探索接发列车作业新模式,保障行车安全具有重要意义。
The traditional train operation at stations is mainly based on human inspection, with high labor intensity and hidden dangers of personal safety, as well as false positive and false negative errors, which makes it difficult to effectively guarantee the quality of train operation. With the application of image recognition, data mining, intelligent analysis and system integration technology, the scheme of in-station train running status monitoring system is proposed,which can automatically collect and intelligently analyze the information of train operation at the station including image, video, wheel tread temperature, vehicle running sound, etc., and provide the recognition and alarm function of vehicle abnormal status. This system can facilitate the transformation of train operation from "human inspection" to "machine inspection", "outdoor inspection" to "indoor inspection", and "static inspection" to "dynamic inspection",which is of great significance to improve the efficiency and quality of train operation at the station and ensure the safety of train operation.
作者
赵周
马福龙
荆长顺
ZHAO Zhou;MA Fulong;JING Changshun(Transportation Department,China Railway Lanzhou Group Co.Ltd.,Lanzhou730000,China;Chengdu Huoan Measurement Technology Center Co.Ltd.,Chengdu 611731,China)
出处
《铁路计算机应用》
2021年第12期56-62,共7页
Railway Computer Application
基金
中国铁路兰州局集团有限公司科研开发课题(lj-700-1000-20210609-3029)。
关键词
监测系统
接发列车作业
车辆限界检测
车轮踏面温度检测
车辆运行异音检测
智能分析
机器学习
monitoring system
receiving and departure train opration
vehicle clearance limit detection
wheel tread temperature detection
abnormal sound detection for vehicle operation
intelligent analysis
machine learning
