The invention discloses a data quality problem discrimination method for traffic signal lamp data acquisition equipment. The method comprises the following steps: S1, determining basic configuration of frequent data quality problem monitoring of the data acquisition equipment; s2, collecting and screening quality monitoring original data of the roadside signal lamp data; s3, reading the number of pieces of monitoring data in the determined frequent data quality problem statistical time period from the database; s4, counting the number of unqualified data in the frequent data quality problem counting time period; s5, calculating the occurrence rate of data quality abnormality; and S6, judging and outputting a frequent data quality problem judgment result. According to the method, on one hand, the data quality problem frequently occurring in the roadside traffic signal lamp data acquisition equipment can be positioned on line; and on the other hand, the equipment which often has data quality problems in the traffic signal lamp data acquisition equipment which is deployed on the roadside in a large scale can be identified on line.

    本发明公开了一种交通信号灯数据采集设备的数据质量问题判别方法,包括步骤S1、确定数据采集设备常发性数据质量问题监测的基本配置;步骤S2、采集并筛选路侧信号灯数据的质量监测原始数据;步骤S3、从数据库中读取已经确定的常发性数据质量问题统计时段内的监测数据条数;步骤S4、统计常发性数据质量问题统计时段内的不合格的数据条数;步骤S5、计算数据质量异常发生率;步骤S6、判断并输出常发性数据质量问题判别结果。通过上述方法,本申请一方面能够在线定位路侧交通信号灯数据采集设备中经常出现的数据质量问题;另一方面能够在线识别已经大规模部署在路侧的交通信号灯数据采集设备中经常出现数据质量问题的设备。


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    Title :

    Data quality problem discrimination method of traffic signal lamp data acquisition equipment


    Additional title:

    一种交通信号灯数据采集设备的数据质量问题判别方法


    Contributors:
    LI XIAOSONG (author) / DING WANTING (author) / SU GUIMIN (author) / WANG YIFAN (author) / LIU JINGXIN (author) / HUANG XIAOYAN (author)

    Publication date :

    2024-10-15


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



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