A dataset of tests in a multiphase experimental plant simulating oil and gas transportation system

The dataset contains measurements collected from an experimental plant configured to simulate an oil and gas transportation system. It includes data recorded under a variety of operating conditions, ranging from normal steady-state behavior to anomalous scenarios such as leakages, obstructions, and deliberate changes in working parameters. These conditions were designed to reflect realistic challenges encountered in actual oil and gas operations. The dataset offers a detailed representation of the system dynamic behavior across different scenarios. It is suitable for developing and testing machine learning models for predictive maintenance and anomaly detection. In control theory, it can support the design and validation of advanced control strategies aimed at maintaining operational safety and efficiency. Furthermore, the dataset facilitates a deeper understanding of the processes governing oil and gas transport, making it a valuable resource for simulation, modeling, and process engineering applications. Funded by the European Union – Next Generation EU under the National Recovery and Resilience Plan (PNRR) – Mission 4 Education and Research – Component 2 From research to business - Investment 1.1, Prin 2022 Notice announced with DD No. 104 of 2/2/2022, Ministero dell’Università e della Ricerca, entitled RESIST - RESilience management to Industrial Systems Threats, proposal code 2022YSAE2X - CUP MASTER: B53D23006650006, CUP: I53D23001940006.本数据集采集自一套配置为模拟油气输送系统的实验装置，包含多种运行工况下的记录数据，覆盖正常稳态运行行为，以及泄漏、堵塞、工作参数蓄意调整等异常场景。上述工况的设置旨在还原实际油气运营中遭遇的真实运维挑战。 本数据集详细刻画了不同场景下系统的动态行为特性，适用于开发和测试面向预测性维护与异常检测的机器学习模型。在控制理论领域，其可支撑旨在保障运行安全与效率的先进控制策略的设计与验证工作。此外，该数据集有助于深入理解油气输送的调控过程，可为模拟、建模及过程工程相关应用提供极具价值的研究资源。 本数据集由欧盟下一代计划（Next Generation EU）资助，依托国家恢复与韧性计划（PNRR）的任务4：教育与研究、组件2：从研究到产业化、投资1.1项目实施。该资助项目依据意大利大学与研究部2022年2月2日第104号通告发布的2022年Prin项目公告设立，项目名称为RESIST——工业系统威胁韧性管理，提案编号为2022YSAE2X，CUP MASTER编号为B53D23006650006，CUP编号为I53D23001940006。