Gas Processing dataset 核心 · 已核验

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"This dataset presents real-time operational parameters acquired from an industrial gas processing facility for the purpose of process monitoring, anomaly detection, predictive maintenance, process optimization, and artificial intelligence applications in oil and gas systems. The dataset contains multivariate time-series measurements collected from major gas processing units including the High-Pressure (HP) Separator, Joule-Thomson Valve (JTV), Low-Pressure (LP) Separator, Gas-to-Gas Exchanger, Chiller Unit, Low-Temperature (LT) Separator, Stabilizer Tower\/Reboiler, and Crude\/Condensate Cooling System.The recorded parameters include pressure, temperature, flow rate, condensate level, interface level, propane boot level, reboiler temperature, stabilizer pressure, and associated process variables measured through industrial field instruments such as pressure indicators (PI\/PIT), temperature indicators (TI), flow indicators (FI\/FIT), and level indicators (LI\/LIT). The dataset also captures abnormal and missing operational conditions represented by entries such as \u201cfaulty\u201d and \u201cN\/A,\u201d thereby making it suitable for fault diagnosis, cyber-physical anomaly detection, sensor validation, and machine learning-based industrial analytics.This dataset is valuable for researchers and engineers working in industrial automation, SCADA systems, process control, digital twin development, predictive analytics, federated learning, and intelligent monitoring of gas processing facilities. It can be applied to the development and validation of deep learning models such as Long Short-Term Memory (LSTM), Autoencoders, Generative Adversarial Networks (GANs), Transformer models, and hybrid AI frameworks for industrial process optimization and early fault detection.The dataset supports reproducible research in Industry 4.0 and smart oil and gas operations by providing realistic process measurements from a complex industrial environment. It is particularly useful for academic research, industrial case studies, and benchmarking of anomaly detection and predictive maintenance algorithms in process engineering applications."

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落地页

https://ieee-dataport.org/documents/gas-processing-dataset

国内可访问性

国内直连:可达 (2026-07-11 检测) 非直连:可达 (2026-07-11 检测)
「直连超时」表示检测窗口内未完成,系慢或不稳定证据,不构成封锁证据。

设备类型

industrial_process

PHM 任务

condition_monitoring anomaly_detection fault_diagnosis fault_detection

传感器