"Open multimodal dataset for rolling bearing degradation" 核心 · 已核验

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"This dataset contains multimodal measurements acquired from an electromechanical drivetrain test bench under stable operating and loading conditions. The dataset includes raw vibration acceleration signals, acoustic emission signal parameters, temperature measurements, applied load, motor torque, and rotational speed records collected simultaneously from multiple sensors installed on the test setup. The measurements were obtained during long-term experiments. The combination of high-frequency sensing data and operational parameters enables research in condition monitoring, fault diagnosis, predictive maintenance, anomaly detection, and machine learning for industrial systems. By providing synchronized measurements from multiple sensing modalities, the dataset supports the development and validation of advanced signal processing techniques, feature extraction methods, data fusion approaches, and artificial intelligence algorithms for machinery health assessment. The dataset can also serve as a benchmark resource for comparative studies and the evaluation of novel diagnostic and prognostic methodologies for rotating machinery and electromechanical systems."

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落地页

https://ieee-dataport.org/documents/open-multimodal-dataset-rolling-bearing-degradation

国内可访问性

国内直连:需登录 (2026-07-11 检测) 非直连:需登录 (2026-07-11 检测)
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设备类型

rolling_bearing

PHM 任务

condition_monitoring fault_diagnosis anomaly_detection health_state_assessment