摘要:工务专业设施的运维管理是铁路运维管理的重要组成部分，传统的工务运维管理受制于技术手段，对图像数据的管理水平较低：采集时效率低；存储时缺乏统一标准，难以长期积累；使用时检索查询不便，限制了工务运维的精准度和效率的进一步提升。本文针对工务运维中图像数据的管理问题，以BIM技术和机器视觉技术为基础，以移动智能终端为载体，研究了工务运维图像数据智能化管理方法。基于机器视觉技术，实现了通过图像识别工务设施，在采集时根据图像内容对图像数据快速分类。基于BIM技术，建立工务运维BIM模型，将工务设施与BIM模型关联起来，为图像数据的分类管理提供可视化平台。基于数据库技术，建立工务设施图像数据库，并将数据库与BIM模型关联起来，实现了运维作业时高效检索查询图像数据。实际应用表明：本文提出的工务运维图像数据管理方法采集效率高，分类规则合理，作业中检索查询便捷，有效地提升了工务运维的效率和精准度，且该方法拓展性较强，对铁路运维智能化发展具有十分重要的意义。

Abstract: The Facility Management of professional public works facilities is an important part of railway operation. The traditional method is restricted by technical means, which is low in image data management, collection efficiencies, and lack of long-time storage standard, which will cause inconvenient during the indexing process. These gaps limit the further improvement regarding to the efficiencies and accuracies during the facility management.Focusing on the image data management during the operation process, based on BIM technology and machine vision technology, using mobile smart terminals as the carrier, this paper studies the intelligent management method of image data operation and maintenance. Based on machine vision technology, it achieves the recognition of facilities via images and the rapid classification of image data via the content of the images during collection. Based on BIM technology, BIM model for facility management are being established, which can associate facilities with the BIM model, and provide a visual platform for the classification and management of image data. Based on database technology, an image database of facilities is being established, and the database is being associated with the BIM model to achieve efficient retrieval and query of image data during operation and maintenance operations. Practical application shows that the image data management method of public works operation and maintenance proposed in this paper has high collection efficiency, reasonable classification rules, convenient retrieval and query in operation, which can effectively improves the efficiency and accuracy of public works operation and maintenance. In addition, this method has strong expansibility and is of great significance to the intelligent development of railway operation and maintenance.