Additional Tennessee Eastman Process Simulation Data for Anomaly Detection

Additional Tennessee Eastman Process Simulation Data for Anomaly Detection 核心 · 已核验

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<h3> Description </h3>

<p>This dataverse contains the data referenced in Rieth et al. (2017). Issues and Advances in Anomaly Detection Evaluation for Joint Human-Automated Systems. To be presented at Applied Human Factors and Ergonomics 2017.

<p>Each .RData file is an external representation of an R dataframe that can be read into an R environment with the 'load' function. The variables loaded are named ‘fault_free_training’, ‘fault_free_testing’, ‘faulty_testing’, and ‘faulty_training’, corres

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落地页: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/6C3JR1
许可证: CC0-1.0 (置信:verified_official)
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发布年份: 2017
发布方: Harvard Dataverse
别名: TEP
设备类型: industrial_process
PHM 任务: fault_detection anomaly_detection

故障工况

传感器

运行工况

关联论文(3944 篇)

仅表示这篇论文与本数据集在文献网络中相邻, 不代表该论文确实使用了本数据集。

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仅列前 20 篇(首发/综述优先,按年份倒序);全量见 API。

溯源(10 条)