铁路基础设施检测监测数据质量评价综述OA

The quality of railway infrastructure inspection and monitoring data is a crucial prerequisite for ensuring train operation safety and enabling intelligent operation and maintenance.This study constructed an analytical framework encompassing"general theory,industry reference,and railway adaptation"and systematically reviewed the research progress in data quality assessment.By focusing on three core dimensions,including the diversified selection of assessment perspectives,the professional construction of assessment indicators,and the intelligent iteration of assessment methods,this study elucidated the pathways and challenges involved in adapting generic frameworks to railway-specific scenarios.The results show that current assessment approaches face several challenges,including an incomplete theoretical system,a lack of professional indicators,and insufficient integration between assessment methods and operational practices.Therefore,it is proposed that a systematic,multi-perspective assessment framework be established,industry-specific quantitative,process,and efficiency indicators be developed,and domain knowledge-guided hybrid intelligent assessment methods be promoted to further integrate data quality assessment with improvement in maintenance performance.This study provides theoretical support for establishing a quality assessment system for railway infrastructure inspection and monitoring data.