管道泄漏、第三方破坏综合性预判测试数据

为了攻克多源数据融合分析技术，创建“多源数据融合—智能感知—自主决策”云边协同模式，基于宏/微观数据融合的油气管道本体结构性缺陷诊断技术研究以及基于多源数据知识模型的线路隐患感知与健康状态评估技术研究，为了保证算法准确性，开展了相关试验并搜集分布式光纤、光纤MEMS等相关数据——主要记录“管道泄漏、第三方破坏综合性预判测试数据”（管道泄漏光纤预判训练数据、管道泄漏光纤预判测试数据、管道泄漏次声预判训练数据、管道泄漏次声预判测试数据、第三方破坏预判测试数据）。“管道泄漏、第三方破坏综合性预判测试数据”面向油气管道本体结构性缺陷诊断技术研究和线路隐患感知与健康状态评估技术研究。To address multi-source data fusion analysis technologies and establish the cloud-edge collaboration mode of "multi-source data fusion – intelligent perception – autonomous decision-making", this work focuses on two core research directions: the structural defect diagnosis technology for oil and gas pipeline bodies based on macro-micro data fusion, and the line hidden danger perception and health status assessment technology based on multi-source data knowledge models. To ensure the accuracy of the developed algorithms, relevant experiments were conducted, and related data including distributed optical fiber and fiber-optic MEMS data were collected. The primary collected dataset is the "comprehensive pre-judgment test data for pipeline leakage and third-party damage", which includes optical fiber-based pre-judgment training data for pipeline leakage, optical fiber-based pre-judgment test data for pipeline leakage, infrasound-based pre-judgment training data for pipeline leakage, infrasound-based pre-judgment test data for pipeline leakage, and pre-judgment test data for third-party damage. This dataset is targeted at the research of structural defect diagnosis technology for oil and gas pipeline bodies and the research of line hidden danger perception and health status assessment technology.

搜集汇总

背景与挑战

背景概述

该数据集为管道泄漏和第三方破坏的综合性预判测试数据，旨在支持多源数据融合分析技术，用于油气管道本体结构性缺陷诊断和线路隐患感知与健康状态评估研究。数据包含分布式光纤、光纤MEMS等相关测试记录，以辅助算法准确性验证。