光纤振动数据集
收藏资源简介:
本数据集专用于训练和优化长输油气管道光纤震动算法模型,旨在智能、精准地识别所辖管道范围内的第三方施工类型并精准定位施工位置。 应用目标为服务于长输油气管道第三方施工监测工作。通过光纤振动数据集与分析模型集成于光纤振动平台,实现对所辖范围内管道的7X24小时自动化监测。 具体流程为:系统自动发现问题 -> 确定类型及位置 -> 报警推送 -> 现场核查验收。本应用有效改变了长输管道依赖人工巡线的传统模式,大幅提升了第三方施工的发现效率、处置速度的精细化管理水平,为保障管道安全平稳运行提供关键技术支撑。
This dataset is specifically designed for training and optimizing fiber-optic vibration algorithm models for long-distance oil and gas pipelines, aiming to intelligently and accurately identify the types of third-party construction within the scope of the managed pipelines and precisely locate the construction positions. Its application objective is to support third-party construction monitoring work for long-distance oil and gas pipelines. By integrating the fiber-optic vibration dataset and analysis model into the fiber-optic vibration platform, 7×24-hour automated monitoring of the pipelines under its management can be realized. The specific workflow is as follows: the system automatically detects problems → identifies the construction type and location → pushes alarm notifications → conducts on-site verification and acceptance. This application has effectively changed the traditional manual patrol-based mode for long-distance pipelines, greatly improving the discovery efficiency of third-party construction, accelerating the disposal speed, and enhancing the refined management level, providing critical technical support for ensuring the safe and stable operation of the pipelines.



